Adjusting insulin delivery rates

ABSTRACT

A method may include generating a first plurality of insulin delivery profiles that include a first series of insulin delivery actions spanning a first time interval, projecting a first plurality of future blood glucose values for each profile of the first plurality of profiles using up-to-date blood glucose levels, selecting one of the first plurality of profiles based upon comparing future blood glucose values for each profile and target blood glucose levels, delivering insulin for a second time interval that corresponds to a first action of the first profile, generating a second plurality of insulin delivery profiles for a third time interval, projecting a second plurality of future blood glucose values for each profile of the second plurality of profiles for the third time interval, and delivering a second dose of insulin for a fourth time interval shorter than the third time interval.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/406,313, filed Jan. 13, 2017, now U.S. Pat. No. 10,307,538, issued onJun. 4, 2019 the disclosure of which is hereby incorporated herein inits entirety by this reference. A claim for benefit of priority to theJan. 14, 2016 filing date of the U.S. Patent Provisional Application No.62/278,978, titled “SYSTEMS AND METHODS FOR CHANGING TARGET GLUCOSEVALUES IN DIABETES MANAGEMENT SYSTEM” (the '978 ProvisionalApplication), and the May 23, 2016 filing date of the U.S. PatentProvisional Application No. 62/340,470, titled “SYSTEMS AND METHODS FORADJUSTING INSULIN DELIVERY RATES” (the '470 Provisional Application), ishereby made pursuant to 35 U.S.C. § 119(e). The entire disclosures andcontents of the '978 Provisional Application and the '470 ProvisionalApplication are hereby incorporated herein in their entirety by thisreference.

FIELD

This document relates to adjusting insulin delivery rates.

BACKGROUND

Diabetes mellitus is a chronic metabolic disorder caused by an inabilityof a person's pancreas to produce sufficient amounts of the hormone,insulin, such that the person's metabolism is unable to provide for theproper absorption of sugar and starch. This failure leads tohyperglycemia, i.e., the presence of an excessive amount of glucosewithin the blood plasma. Persistent hyperglycemia has been associatedwith a variety of serious symptoms and life threatening long-termcomplications such as dehydration, ketoacidosis, diabetic coma,cardiovascular diseases, chronic renal failure, retinal damage and nervedamages with the risk of amputation of extremities. Because healing isnot yet possible, a permanent therapy is necessary that providesconstant glycemic control in order to constantly maintain the level ofblood glucose within normal limits. Such glycemic control is achieved byregularly supplying external drugs to the body of the patient to therebyreduce the elevated levels of blood glucose.

Historically, diabetes is treated with multiple, daily injections ofrapid and long acting insulin via a hypodermic syringe. One or twoinjections per day of a long acting insulin is administered to provide abasal level of insulin and additional injections of a rapidly actinginsulin is administered before or with each meal in an amountproportional to the size of the meal. Insulin therapy can also beadministered using an insulin pump that provides periodic or continuousrelease of the rapidly acting insulin to provide for a basal level ofinsulin and larger doses of that same insulin at the time of meals.Insulin pumps allow for the delivery of insulin in a manner that bearsgreater similarity to the naturally occurring physiological processesand can be controlled to follow standard or individually modifiedprotocols to give the patient better glycemic control. In somecircumstances, an insulin pump device can store (via input from aclinician or a user) a number of settings (e.g., dosage parameters orother settings) that are customized by the physician for the particularuser.

People with diabetes, their caregivers, and their health care providers(HCPs) bear a great deal of cognitive burden in managing intensivemedicine therapy. Delivering the correct amount of the medicine at thecorrect time is an extremely challenging endeavor. Such deliveryrequires the patient to make dosing determinations multiple times perday and also requires a combination of the patient and the HCP torecalibrate the therapeutic parameters of the therapy on an episodictime frame that varies from individual to individual, and withinindividuals based on age and/or behavior (e.g., change in exercise,change in diet).

In light of the many deficiencies and problems associated with currentsystems and methods for maintaining proper glycemic control, enormousresources have been put into finding better solutions. A number of newtechnologies promise to mitigate some of the cognitive burden thatintensive insulin therapy now requires. Developing workable solutions tothe problem that are simple, safe, reliable and able to gain regulatoryapproval has, however, proved to be elusive. For years, researchers havecontemplated coupling a continuous glucose monitoring system with aninsulin delivery device to provide an “artificial pancreas” to assistpeople living with diabetes. Their efforts have yet to result in acommercial product. What has been needed is a system and method thatprovides a level of automatic control of drug delivery devices forimproved medicine delivery and glycemic control that is simple, safe,and reliable in a real world setting.

SUMMARY

Methods and systems provided herein simplify the delivery of basalinsulin, which can reduce the cognitive burden for managing diabetes fora user (e.g., a patient, caretaker, or clinician).

In one or more embodiments, the present disclosure may include a methodthat includes generating a first plurality of insulin delivery profiles.Each of the first plurality of insulin delivery profiles may include afirst series of insulin delivery actions spanning a first time interval.The method may also include projecting a first plurality of future bloodglucose values for each insulin delivery profile of the first pluralityof insulin delivery profiles for a plurality of times spanning the firsttime interval. Each projected future blood glucose value may beprojected using at least one up-to-date blood glucose level for a personwith diabetes (PWD). The method may additionally include selecting afirst profile of the first plurality of insulin delivery profiles basedat least in part upon a comparison between the first plurality of futureblood glucose values for each insulin delivery profile and at least onetarget blood glucose level. The method may also include delivering afirst dose of insulin using an insulin pump for a second time intervalafter a previous dose of insulin that corresponds to a first action (ora series of first actions) in the first series of insulin deliveryactions of the first profile. The second time interval may be shorterthan the first time interval. The method may also include generating asecond plurality of insulin delivery profiles for a time periodextending from the end of the second time interval for a third timeinterval, and projecting a second plurality of future blood glucosevalues for each insulin delivery profile of the second plurality ofinsulin delivery profiles for a plurality of times spanning the thirdtime interval. The method may also include delivering a second dose ofinsulin using the insulin pump for a fourth time interval after the endof the second time interval. The fourth time interval may be shorterthan the third time interval.

In accordance with one or more methods of the present disclosure, thefirst series of insulin delivery actions may include delivering insulinat multiples, ratios, or a combination thereof of a baseline basalinsulin rate.

In accordance with one or more methods of the present disclosure, thefirst series of insulin delivery actions may include delivering insulinat between Ox and 3 x the baseline basal insulin rate (inclusive ofendpoints).

In accordance with one or more methods of the present disclosure, thefirst plurality of insulin delivery profiles may include between 5profiles and 100 profiles. In such cases, at least one profile maydeliver insulin at Ox baseline basal rate for at least the second timeinterval, at least one profile may deliver insulin at the baseline basalrate for at least the second time interval, and at least one profile maydeliver insulin at 2× baseline basal rate for at least the second timeinterval.

In accordance with one or more methods of the present disclosure, atleast one of the first plurality of insulin delivery profiles mayinclude an inflection point between a first insulin delivery amount fora first portion of the first series of insulin delivery actions and asecond insulin delivery amount for a second portion of the first seriesof insulin delivery actions.

In accordance with one or more methods of the present disclosure, thefirst time interval may be at least 2 hours and no more than 6 hours andthe second time interval may be at least 5 minutes and no more than 90minutes.

In accordance with one or more methods of the present disclosure, thefirst time interval may be at least 2.5 hours and no more than 5.5 hoursand the second time interval may be at least 7.5 minutes and no morethan 60 minutes.

In accordance with one or more methods of the present disclosure, thefirst time interval may be least 3 hours and no more than 5 hours andthe second time interval may be at least 10 minutes and no more than 30minutes.

In accordance with one or more methods of the present disclosure, thefirst profile of the first plurality of insulin delivery profiles may beselected based on a calculated cost function for each of the firstplurality of insulin delivery profiles.

In accordance with one or more methods of the present disclosure, thefirst profile may be selected based on having the lowest cost function.In such cases, differences between each projected future blood glucoselevel and one or more target blood glucose levels may increase acalculated cost function value for each insulin delivery profile.

In accordance with one or more methods of the present disclosure, thecost function value increase may be greater for differences where theprojected blood glucose level is below the target blood glucose levelcompared to equal magnitude differences where the projected bloodglucose level is above the target blood glucose level.

In accordance with one or more methods of the present disclosure, thecost function may include a bias or insulin delivery profiles thateither maintain a delivery of insulin at a rate equal to the previouslydelivered rate, or that deliver insulin at a baseline basal rate.

In accordance with one or more methods of the present disclosure,predicting future blood glucose may include determining an effect onblood glucose due to carbohydrates, and determining an effect on bloodglucose due to insulin.

In accordance with one or more methods of the present disclosure, theeffect on blood glucose due to carbohydrates may be determined using theequation

$G_{c} = {\frac{{K_{c}\left( {1 - \alpha_{c}} \right)}B^{C_{dt}}}{\left( {1 - {\alpha_{c}B}} \right)\left( {1 - B} \right)}.}$

In accordance with one or more methods of the present disclosure, theeffect on blood glucose due to insulin may be determined using theequation

$G_{i} = {\frac{{K_{i}\left( {1 - \alpha_{c}} \right)}B^{i_{dt}}}{\left( {1 - {\alpha_{i}B}} \right)\left( {1 - B} \right)}.}$

In accordance with one or more methods of the present disclosure,predicting future blood glucose may include determining the effect ofinsulin on board and carbohydrates on board.

In accordance with one or more methods of the present disclosure, theplurality of glucose sensor data points may be obtained from one of acontinuous glucose monitor (CGM) or a blood glucose monitor (BGM).

In one or more embodiments, the present disclosure may include a systemthat includes a glucose configured to generate a plurality of glucosesensor data points, and a control device. The control device may beconfigured to generate a first plurality of insulin delivery profiles,and each of the first plurality of insulin delivery profiles may includea first series of insulin delivery actions spanning a first timeinterval. The control device may also be configured to project a firstplurality of future blood glucose values for each insulin deliveryprofile of the first plurality of insulin delivery profiles for aplurality of times spanning the first time interval, and each of theprojected future blood glucose values may be projected using at leastone up-to-date blood glucose level from the glucose sensor. The controldevice may additionally be configured to select a first profile of thefirst plurality of insulin delivery profiles based at least in part upona comparison between the first plurality of future blood glucose valuesfor each insulin delivery profile and at least one target blood glucoselevel. The control device may also be configured to generate a signal todeliver a first dose of insulin for a second time interval after aprevious dose of insulin. The first dose of insulin may correspond to afirst action in the first series of insulin delivery actions of thefirst profile, and the second time interval may be shorter than thefirst time interval. The control device may additionally be configuredto generate a second plurality of insulin delivery profiles for a timeperiod extending from the end of the second time interval for a thirdtime interval, and to project a second plurality of future blood glucosevalues for each insulin delivery profile of the second plurality ofinsulin delivery profiles for a plurality of times spanning the thirdtime interval. The control device may also be configured to select asecond profile of the second plurality of insulin delivery profilesbased at least in part upon a comparison between the second plurality offuture blood glucose values for each insulin delivery profile and atleast one target blood glucose level. The control device mayadditionally be configured to generate a signal to deliver a second doseof insulin using the insulin pump for a fourth time interval after theend of the second time interval, the fourth time interval being shorterthan the third time interval. The system may also include an insulinpump configured to deliver insulin based on the signal of the controldevice.

In accordance with one or more systems of the present disclosure, thecontrol device may include a communication device to transmit theplurality of glucose sensor data points to a computing device.

In accordance with one or more systems of the present disclosure, thefirst plurality of insulin delivery profiles may include between 5profiles and 100 profiles. In such cases, at least one profile maydeliver insulin at Ox the baseline basal rate for at least the secondtime interval, at least one profile may deliver insulin at the baselinebasal rate for at least the second time interval, and at least oneprofile may deliver insulin at 2× the baseline basal rate for at leastthe second time interval.

In accordance with one or more systems of the present disclosure, thefirst time interval may be at least 3 hours and no more than 5 hours andthe second time interval may be at least 10 minutes and no more than 30minutes.

In one or more embodiments, the present disclosure may include a methodincluding delivering insulin, using an insulin pump and a controller,over a first diurnal time period based on a baseline basal insulin ratestored in memory. The controller may receive blood glucose data tocontrol delivery of insulin via the insulin pump in amounts variablefrom the baseline basal insulin rate to control blood glucose levels fora person with diabetes (PWD). The method may also include modifying thebaseline basal insulin rate stored in the memory for a second diurnaltime period that is at least 20 hours after the first diurnal periodbased on an amount of insulin actually delivered during the firstdiurnal time period.

In accordance with one or more methods of the present disclosure, acarbohydrate-to-insulin ratio (CR) for the second diurnal time periodmay also be modified based on the amount of insulin actually deliveredduring the first diurnal time period.

In accordance with one or more methods of the present disclosure, aninsulin sensitivity factor (ISF) for the second diurnal time period mayalso be modified based on the amount of insulin actually deliveredduring the first diurnal time period.

In accordance with one or more methods of the present disclosure, thesecond diurnal time period may include one of a same time period onanother day or a time period within two hours prior to the same timeperiod on another day.

In accordance with one or more methods of the present disclosure, thebaseline basal insulin rate stored in memory for the second diurnal timeperiod may be increased if a ratio of the amount of insulin actuallydelivered during the first diurnal time period to the amount dictated bythe baseline basal insulin rate for the first diurnal time periodexceeds a predetermined first threshold. Additionally, the baselinebasal insulin rate stored in memory for the second diurnal time periodmay be decreased if the ratio falls below a predetermined secondthreshold.

In accordance with one or more methods of the present disclosure, thebaseline basal insulin rate stored in memory for the second diurnal timeperiod may be increased or decreased by a fixed amount or percentagethat is less than the difference between the amount of insulin actuallydelivered during the first diurnal time period and the amount dictatedby the baseline basal insulin rate.

In accordance with one or more methods of the present disclosure, thebaseline basal rate stored in memory may be increased or decreased by apercentage between about 1% and about 5%.

In accordance with one or more methods of the present disclosure, astored CR or a stored ISF for the second diurnal time period may also beincreased or decreased by a fixed amount or percentage when the baselinebasal rate is modified.

In accordance with one or more methods of the present disclosure, thebaseline basal rate, CR, and ISF stored in memory may each be increasedor decreased by a percentage between about 1% and about 5%. In somecases, each of CR, ISF, and BBR are each increased/decreased in lockstep, with each of CR and ISF being increased by a percentageapproximately equal to the percentage of a decrease to BBR for whenthere is a decrease in the BBR and each of CR and ISF being decreased bya percentage approximately equal to the percentage of an increase to BBRfor when there is an increase in the BBR. In some cases, CR, ISF, andBBR can all be increased/decreased based on a predeterminedrelationship.

In accordance with one or more methods of the present disclosure, thebaseline basal insulin rate stored in memory may be adjusted by anamount that is based on the ratio, but less than the difference betweenthe amount of insulin actually delivered during the first diurnal timeperiod and the amount dictated by the baseline basal insulin rate.

In accordance with one or more methods of the present disclosure, astored CR and a stored ISF for the second diurnal time period may beincreased when the basal rate is decreased and may be decreased when thebasal rate is increased.

In accordance with one or more methods of the present disclosure,delivering insulin, using an insulin pump and controller, over a firstdiurnal time period may include generating a first plurality of insulindelivery profiles that each include a first series of insulin deliveryactions spanning a first time interval and based on the baseline basalinsulin rates stored in memory for a plurality of diurnal time periodswithin the first time interval. Delivering insulin may additionallyinclude projecting a first plurality of future blood glucose values foreach insulin delivery profile of the first plurality of insulin deliveryprofiles for a plurality of times spanning the first time interval, andeach of the projected future blood glucose values may be projected usingat least one up-to-date blood glucose level for the PWD. Deliveringinsulin may also include selecting a first profile of the firstplurality of insulin delivery profiles based at least in part upon acomparison between the first plurality of future blood glucose valuesfor each insulin delivery profile and at least one target blood glucoselevel. Delivering insulin may additionally include delivering a firstdose of insulin for at least part of the first diurnal time period usingthe insulin pump for a second time interval, the second time intervalbeing no greater than the first diurnal time period, and optionallyrepeating these steps until insulin is delivered for the entire firstdiurnal time period.

In accordance with one or more methods of the present disclosure, eachaction in the first series of insulin delivery actions may include oneof delivering Ox, lx, or 2 x the baseline basal insulin rate.

In accordance with one or more methods of the present disclosure, theplurality of future blood glucose levels may be determined using an ISF,CR, or combination thereof stored in memory for the first diurnal timeperiod.

In accordance with one or more methods of the present disclosure, thecontroller may receive insulin or food consumption data to controldelivery of insulin.

In one or more embodiments, the present disclosure may include a systemthat includes an insulin pump configured to deliver insulin based on amessage, a glucose sensor configured to generate blood glucose data, anda controller including memory. The controller may be configured togenerate messages to deliver insulin over a first diurnal time periodbased on a baseline basal insulin rate stored in the memory. Thecontroller may also be configured to receive blood glucose data from theglucose sensor to control generation of the messages to deliver insulinin amounts variable from the baseline basal insulin rate to controlblood glucose levels for a person with diabetes (PWD). The controllermay additionally be configured to modify the baseline basal insulin ratestored in the memory for a second diurnal time period that is at least20 hours after the first diurnal period based on an amount of insulinactually delivered during the first diurnal time period.

In accordance with one or more systems of the present disclosure, thecontroller may be part of the insulin pump.

In accordance with one or more systems of the present disclosure, thecontroller may be a separate device from the insulin pump.

In one or more embodiments, the present disclosure may include a methodthat includes displaying to a user an interface at which the user inputsa fear of hypoglycemia index (FHI), the FHI corresponding to anacceptable probability of a blood glucose level being below a thresholdblood glucose level. The method may also include receiving blood glucosedata for a person with diabetes (PWD). The method may additionallyinclude calculating a probability of the PWD having a blood glucoselevel below the threshold blood glucose level based on the variabilityof the received blood glucose data. The method may also include settingone or more target blood glucose levels to align the probability of thePWD having a blood glucose level below the threshold blood glucose levelwith the acceptable probability associated with the user input FHI. Themethod may additionally include delivering insulin, using the insulindelivery device, based on the target blood glucose level.

In accordance with one or more methods of the present disclosure, aplurality of target blood glucose levels may be set for a plurality ofdiurnal time periods and independently modified for each diurnal timeperiod based on a calculated probability of the PWD having a bloodglucose level falling below the threshold blood glucose level duringthat diurnal time period.

In accordance with one or more methods of the present disclosure, theinsulin delivery device is an insulin pump.

In accordance with one or more methods of the present disclosure,delivering insulin, using the insulin pump, based on the one or moretarget blood glucose levels may include generating a first plurality ofinsulin delivery profiles, where each of the first plurality of basalinsulin delivery profiles may include a first series of insulin deliveryactions spanning a first time interval. Delivering insulin may alsoinclude selecting a first profile of the first plurality of basalinsulin delivery profiles that approximates the one or more target bloodglucose level based on projected blood glucose levels for each of theplurality of insulin delivery profiles. Delivering insulin mayadditionally include delivering a dose of insulin using the insulin pumpfor a second time interval after a previous dose of insulin, the dose ofinsulin corresponding to a first action in the first series of insulindelivery actions of the first profile, and the second time intervalbeing shorter than the first time interval.

In accordance with one or more methods of the present disclosure, thefirst plurality of basal insulin delivery profiles may each be evaluatedusing a cost function that evaluates the differences between theprojected blood glucose levels and the one or more target blood glucoselevels, and the first profile may be selected based on the costfunction.

In accordance with one or more methods of the present disclosure, theuser interface may include an interactive feature with a plurality ofpossible FHI values by which the user inputs the FHI by selecting adisplayed possible FHI.

In accordance with one or more methods of the present disclosure, theFHI options displayed include at least one of a numerical blood glucoselevel, a probability of going below a low threshold glucose level, aprobability of going above a high threshold glucose level, and a textualdescription of a preferred glucose level, by which the user inputs theFHI.

In accordance with one or more methods of the present disclosure, theuser may be the PWD, a caregiver to the PWD, or a healthcareprofessional.

In one or more embodiments, the present disclosure may include a systemthat includes an interactive display device configured to display aninterface at which the user inputs a fear of hypoglycemia index (FHI).The FHI may correspond to an acceptable probability of crossing athreshold blood glucose level. The system may also include an insulinpump configured to deliver insulin based on a message, and a controldevice configured to calculate a probability of a person with diabetes(PWD) having a blood glucose level that falls below the threshold bloodglucose level based on the variability of blood glucose levels for thatPWD. The controller may also be configured to determine, based on theFHI and the probability of the PWD crossing the threshold blood glucoselevel, one or more target blood glucose levels to align the probabilityof the PWD having a blood glucose level that falls below the thresholdblood glucose level with the acceptable probability associated with auser selected FHI. The controller may additionally be configured todetermine an insulin delivery profile or rate based on the one or moretarget blood glucose levels, and generate the message to the insulinpump to deliver insulin based on the determined insulin delivery profileor rate.

In accordance with one or more systems of the present disclosure, theinteractive display device and the control device may be components ofthe same device.

In accordance with one or more systems of the present disclosure, theinteractive display device and the control device may be components ofdifferent devices.

In accordance with one or more systems of the present disclosure, thecontroller may store a plurality of target blood glucose levels for aplurality of diurnal time periods and may independently modify eachdiurnal time period based on a calculated probability of the PWD havinga blood glucose level falling below the threshold blood glucose levelduring that diurnal time period.

In accordance with one or more systems of the present disclosure, thecontroller may determine an insulin delivery profile or rate bygenerating a first plurality of insulin delivery profiles, where each ofthe first plurality of basal insulin delivery profiles may include afirst series of insulin delivery actions spanning a first time interval.The controller may also determine an insulin delivery profile or rate byselecting a first profile of the first plurality of basal insulindelivery profiles that approximates the one or more target blood glucoselevels based on projected blood glucose levels for each of the pluralityof insulin delivery profiles. In such a case, generating the message maybe further based on a dose of insulin corresponding to a first action inthe first series of insulin delivery actions of the first profile, andthe second time interval may be shorter than the first time interval.

In accordance with one or more systems of the present disclosure, thefirst plurality of basal insulin delivery profiles may each be evaluatedusing a cost function evaluating the differences between the projectedblood glucose levels and at least the one or more target blood glucoselevels, and the first profile may be selected based on the costfunction.

In accordance with one or more systems of the present disclosure, theuser interface may include an interactive feature with a plurality ofpossible FHI values by which the user inputs the FHI.

In accordance with one or more systems of the present disclosure, theFHI options displayed may include at least one of a numerical bloodglucose level, a probability of going below a low threshold glucoselevel, a probability of going above a high threshold glucose level, anda textual description of a preferred glucose level, by which the userinputs the FHI.

In one or more embodiments, the present disclosure may include anon-transitory computer readable medium containing instructions that,when executed by a processor, are configured to perform operations. Theoperations may include receiving a selection of a fear of hypoglycemiaindex (FHI), where the FHI may correspond to an acceptable probabilityof crossing a threshold blood glucose level. The operations may alsoinclude calculating a probability of a person with diabetes (PWD) havinga blood glucose level falling below the threshold blood glucose levelbased on variability of blood glucose values for the PWD. The operationsmay additionally include setting, based on the FHI and the probabilityof the PWD having a blood glucose level falling below the thresholdblood glucose level, one or more target blood glucose levels to alignthe probability of the PWD having a blood glucose level falling belowthe threshold blood glucose level with the acceptable probabilityassociated with a user selected FHI. The operations may additionallyinclude generating a message to an insulin pump to deliver insulin basedon the one or more target blood glucose levels.

In one or more embodiments, the present disclosure may include a methodthat includes receiving up-to-date blood glucose data for a person withdiabetes (PWD), and determining basal insulin dosages for the PWD basedat least in part on one or more baseline basal rates stored in memory ona controller, with the received up-to-date blood glucose data and atleast one target blood glucose level stored in the memory. The methodmay also include delivering one or more of the determined basal insulindosages to the PWD, and modifying the one or more target blood glucoselevels stored in the memory based on a variability of blood glucose datafor the PWD. The method may also include receiving an input at anelectronic device of a temporary override indicating a user preferenceto reduce the likelihood that the PWD has a hypoglycemic event or a userpreference to reduce the likelihood that the PWD has a hyperglycemicevent. The method may also include determining one or more temporarytarget blood glucose levels based on the received user input, where thetemporary target blood glucose levels may be greater than the modifiedone or more target blood glucose levels if the user preference is toreduce the likelihood that the PWD has a hypoglycemic event.Alternatively, the temporary target blood glucose levels may be lowerthan the modified one or more target blood glucose levels if the userpreference is to reduce the likelihood that the PWD has a hyperglycemicevent. The method may additionally include delivering one or more dosesof basal insulin for the temporary period of time based on the one ormore temporary target blood glucose levels.

In accordance with one or more methods of the present disclosure, thebasal insulin dosages for the PWD may be determined by generating afirst plurality of insulin delivery profiles, where each of the firstplurality of insulin delivery profiles may include a first series ofinsulin delivery actions based on the one or more stored baseline basalinsulin rates spanning a first time interval. The basal insulin dosagesmay also be determined by projecting a first plurality of future bloodglucose values for each insulin delivery profile of the first pluralityof insulin delivery profiles for a plurality of times spanning the firsttime interval, where each projected future blood glucose values may beprojected using at least one of the received up-to-date blood glucoselevels for the PWD. The basal insulin dosages may additionally bedetermined by selecting a first profile of the first plurality ofinsulin delivery profiles based at least in part upon a comparisonbetween the first plurality of future blood glucose values for eachinsulin delivery profile and the one or more target blood glucoselevels.

In accordance with one or more methods of the present disclosure, thefirst time interval may be longer than the time interval for which theselected first profile is used to deliver insulin prior to thedetermination of a next dose of insulin using the same process.

In accordance with one or more methods of the present disclosure, theprocess of generating a plurality of insulin delivery profiles may beused during the temporary period of time, and the selected profile maybe based on the one or more temporary target blood glucose levels duringthe temporary period of time.

In accordance with one or more methods of the present disclosure,receiving an input may include receiving a selection of one of anumerical target blood glucose level, a selection of an activity, or aselection of a textual description of a preferred blood glucose level.

In accordance with one or more methods of the present disclosure, theone or more temporary target blood glucose levels may be set at a fixedpercentage increase or decrease from the one or more modified targetblood glucose levels, and may be optionally limited by a prestored orparticular maximum or minimum value for target blood glucose levels.

In accordance with one or more methods of the present disclosure, theone or more temporary target blood glucose levels may be set at a fixednumerical increase or decrease from the one or more modified targetblood glucose levels, and may be optionally limited by a prestored orparticular maximum or minimum value for target blood glucose levels.

In accordance with one or more methods of the present disclosure, alltarget blood glucose levels are limited to values between 100 mg/dL and160 mg/dL.

In accordance with one or more methods of the present disclosure,receiving an input may include receiving a length of time for thetemporary period of time.

In accordance with one or more methods of the present disclosure, thememory may store a baseline basal rate and a target blood glucose levelfor a plurality of diurnal time periods.

In accordance with one or more methods of the present disclosure, theone or more target blood glucose levels may be modified based on adetermination of a probability of the PWD having a blood glucose levelbelow a threshold blood glucose level based on the variability ofreceived blood glucose data over multiple days. In such cases, the oneor more target blood glucose levels may be modified to align theprobability of the PWD having a blood glucose level below the thresholdblood glucose level with an acceptable probability of the PWD having ablood glucose level falling below the threshold blood glucose level.

In one or more embodiments, the present disclosure may include a systemthat includes an insulin pump configured to deliver insulin based on amessage, a glucose sensor configured to generate a plurality of glucosesensor data points, an interface for receiving a user preference toreduce the likelihood that a person with diabetes (PWD) has ahypoglycemic event or a user preference to reduce the likelihood thatthe PWD has a hyperglycemic event, and a controller. The controller, theuser interface, or a combination thereof, may be configured to receiveup-to-date blood glucose data from the glucose sensor, and determinebasal insulin dosages based at least in part on one or more baselinebasal rates stored in memory on the controller, where the receivedup-to-date blood glucose data, and at least one target blood glucoselevel may be stored in the memory. The controller, the user interface,or a combination thereof, may additionally be configured to generate themessage to the insulin pump to deliver the determined basal insulindosages, modify the one or more target blood glucose levels stored inthe memory based on a variability of blood glucose data from the glucosesensor, and receive the user preference. The controller, the userinterface, or a combination thereof, may also be configured to determineone or more temporary target blood glucose levels based on the receiveduser preference, where the temporary target blood glucose levels may begreater than the modified one or more target blood glucose levels if theuser preference is to reduce the likelihood that the PWD has ahypoglycemic event. Alternatively, the temporary target blood glucoselevels may be lower than the modified one or more target blood glucoselevels if the user preference is to reduce the likelihood that the PWDhas a hyperglycemic event. The controller, the user interface, or acombination thereof, may also be configured to generate the message tothe insulin pump to deliver doses of basal insulin for the temporaryperiod of time based on the one or more temporary target blood glucoselevels.

In accordance with one or more systems of the present disclosure, thecontroller may be part of the insulin pump.

In accordance with one or more systems of the present disclosure, thecontroller may be a separate device from the insulin pump.

The details of one or more implementations of various embodiments areset forth in the accompanying drawings and the description below. Otherfeatures, objects, and advantages of the various embodiments will beapparent from the description and drawings, and from the claims.

It is to be understood that both the foregoing general description andthe following detailed description are merely examples and explanatoryand are not restrictive of the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

Example embodiments will be described and explained with additionalspecificity and detail through the use of the accompanying drawings inwhich:

FIG. 1 provides an example diabetes management system (DMS);

FIG. 2 is a flowchart of an example technique for adjusting basalinsulin delivery rates;

FIG. 3 illustrates multiple example insulin delivery profiles, projectedblood glucose levels for the profiles, and a “loss” calculation for eachprofile;

FIG. 4 illustrates an example model for calculating future blood glucosevalues;

FIG. 5 illustrates data recorded for a simulated person with diabetesusing methods and systems provided herein;

FIGS. 6A and 6B depict additional details of the example DMS of FIG. 1;

FIG. 7 illustrates a flowchart of an example method of using insulindelivery profiles;

FIG. 8 illustrates a flowchart of an example method of adjusting insulindelivery rates;

FIG. 9 illustrates a flowchart of an example method of utilizing a fearof hypoglycemia index; and

FIG. 10 illustrates a flowchart of an example method of utilizing atemporary override.

DESCRIPTION OF EMBODIMENTS

Medicine delivery systems and methods provided herein may be used andperformed, respectively, by a user, for example, a person with diabetes(PWD). The PWD may live with type 1, type 2, or gestational diabetes. Insome cases, a user can be a healthcare professional or caregiver for aPWD.

Methods and systems provided herein can use information from a glucosemeasurement device (e.g., a continuous glucose monitor) to haveup-to-date blood glucose data (e.g., a plurality of blood glucose datapoints each hour) for the PWD in order to determine how to adjust basalinsulin delivery rates. In some cases, methods and systems providedherein can use blood glucose data from both one or more continuousglucose monitors and one or more blood glucose meters. Methods andsystems provided herein can be part of a hybrid closed-loop system (forexample, where basal rates can be adjusted automatically and the PWD canmanually enter or deliver a bolus). In some cases, methods and systemprovided herein can be part of a fully closed-loop system (for example,where basal rates can be adjusted automatically and boluses can bedelivered automatically). In some cases, “up-to-date” may mean less than1 hour old, less than 30 minutes old, or less than 15 minutes old.

Methods and systems provided herein can use a model to predict multiplefuture blood glucose levels for multiple different basal insulindelivery profiles or basal insulin delivery rates, and select one of thebasal insulin delivery profiles or basal insulin delivery rates based onprediction of which profile or rate will approximate a target bloodglucose level, or more specifically, select the profile that minimizesthe differences between the predicted future blood glucose values andone or more target blood glucose values. In some cases, the profile thatminimizes, lessons, or lowers variations from one or more target bloodglucose levels in the future may be selected. The selected basal profilecan then be delivered to the PWD at least until a process of evaluatingdifferent basal insulin delivery profiles or rates is repeated. In somecases, methods and systems provided herein can repeat a process ofevaluating multiple different basal insulin delivery profiles or basalinsulin delivery rates at a time interval that is less than the timeinterval for the plurality of future predicted blood glucose values. Forexample, in some cases, the time interval between evaluating andselecting from multiple different basal insulin delivery profiles orbasal insulin delivery rates can be less than one hour while theplurality of future predicted blood glucose values can extend over atime interval of at least two hours into the future. In some cases ofmethods and systems provided herein, each of the evaluated basal insulindelivery profiles or rates can extend for a time interval greater thanthe time interval between evaluation processes. In some cases, methodsand systems provided herein can evaluate insulin delivery profiles andrates that extend at least two hours into the future and predicted bloodglucose values can also be predicted over a time interval that extendsat least two hours into the future. In some cases, the profiles/ratesand time interval of predicted future blood glucose values extends atleast three hours into the future. In some cases, the profiles/rates andtime interval of predicted future blood glucose values extends a periodof time (e.g., at least four hours) into the future. In some cases, theprofiles/rates and time interval of predicted future blood glucosevalues extends at least five hours into the future. As used herein, theterm blood glucose level may include any measurement that estimates orcorrelates with blood glucose level, such as a detection of glucoselevels in interstitial fluids, urine, or other bodily fluids or tissues.

The different basal insulin delivery profiles or rates for eachevaluation process can be generated using any suitable techniques. Insome cases, multiple profiles or delivery rates are generated using oneor more user-specific dosage parameters. In some cases, one or moreuser-specific dosage parameters can be entered by a user, calculated byinformation entered by a user, and/or calculated by monitoring datagenerated from the PWD (e.g., monitoring insulin delivery rates andblood glucose data while the PWD is using a pump in an open loop mode).In some cases, methods and systems provided herein can modifyuser-specific dosage parameters over time based on one or more selectedbasal insulin delivery profiles or rates and/or other data obtained fromthe PWD. In some cases, the user-specific dosage parameters can bedosage parameters that are commonly used in the treatment of diabetes,such as average total daily insulin, total daily basal (TDB) insulin,average basal rate, insulin sensitivity factor (ISF), andcarbohydrate-to-insulin ratio (CR). For example, in some cases, a PWD'saverage basal rate can be used to calculate multiple different basalinsulin delivery profiles based on multiples or fractions of the averagebasal rate used over different intervals of time. In some cases, methodsand systems provided herein can use time-interval-specific user-specificdosage parameters (e.g., a time-interval-specific baseline basal rate).In some cases, methods and systems provided herein can make adjustmentsto time-interval-specific user-specific dosage parameters for each timeinterval for where a delivered basal rate varies from a baseline basalrate for that time interval. In some cases, user-specific dosageparameters are specific for time intervals of two hours or less, onehour or less, thirty minutes or less, or fifteen minutes or less. Forexample, in some cases, methods and systems provided herein can store abaseline basal rate for the hour between 1 PM and 2 PM, and can adjustthe baseline basal rate for that hour up if the method or systemdelivers more basal insulin during that time period and adjust thebaseline basal rate down if the method or system delivers less basalinsulin during that time period. In some cases, adjustments touser-specific dosage parameters can be based on a threshold variationand/or can be limited to prevent excessive adjustments to user-specificdosage parameters. For example, in some cases, a daily adjustment to auser-specific dosage parameter can be limited to less than 10%, lessthan 5%, less than 3%, less than 2%, or to about 1%. In some cases, anadjustment to a baseline basal rate is less than a difference betweenthe amount of basal insulin actually delivered and the baseline basalfor a specific period of time (e.g., if a baseline basal rate is 1U/hour and systems or methods provided herein actually delivered 2 U forthe previous hour, the adjustment to any baseline basal rate based onthat difference would be less than 1 U/hour).

Methods and systems provided herein can use any appropriate model topredict multiple future blood glucose values. In some cases, predictivemodels can use one or more current or recent blood glucose measurements(e.g., from blood glucose meter and/or a continuous glucose monitor),estimates of rates of change of blood glucose levels, an estimation ofunacted carbohydrates, and/or an estimation of unacted insulin. In somecases, predictive models can use one or more user-specific dosageparameters in predicting multiple blood glucose values over a futuretime interval for multiple different basal insulin delivery profiles orrates over that same future time interval. As discussed above, thatfuture time interval can be at least two hours, at least three hours, orat least four hours, at least five hours, etc. User-specific dosageparameters, which can be time-interval-specific, can also be used indetermining an estimation of unacted carbohydrates and/or an estimationof unacted insulin. In some cases, an estimation of unactedcarbohydrates and/or an estimation of unacted insulin can use a simpledecay function. In some cases, an estimate of unacted insulin can bedetermined using an Insulin On Board (IOB) calculation, which are commonin the art of treating diabetes. In some cases, an IOB calculation usedin a predictive model used in methods and systems provided herein canconsider insulin delivered to the PWD during the delivery of a bolus. Insome cases, the IOB calculation can additionally add or subtract to theIOB based on changes to the basal insulin delivery rate from a baselinebasal rate. In some cases, an estimate of unacted carbohydrates can bedetermined using a Carbohydrates On Board (COB) calculation, which canbe based on a decay function and announced meals. In some cases,predictive models used in methods and systems provided herein can alsoconsider the non-carbohydrate components of a meal. In some cases,methods and systems provided herein can infer an amount of carbohydratesfrom an unannounced meal due to a spike in up-to-date blood glucosedata. In some cases, predictive models used in methods and systemsprovided herein can additionally consider additional health data orinputs, which may indicate that the PWD is sick, exercising,experiencing menses, or some other condition that may alter the PWD'sreaction to insulin and/or carbohydrates. In some cases, at least anIOB, a COB, an insulin sensitivity factor (ISF), and acarbohydrate-to-insulin ratio (CR) are used to predict future bloodglucose values for each evaluated basal insulin delivery profile orrate.

Methods and systems provided herein can set one or more blood glucosetargets using any suitable technique. In some cases, a blood glucosetarget can be fixed, either by a user or preprogrammed into the system.In some cases, the target blood glucose level can be time intervalspecific (e.g., based on diurnal time segments). In some cases, a usercan temporarily or permanently adjust the target blood glucose level. Insome cases, methods and systems provided herein can analyze thevariability of blood glucose data for specific days of the week and/orbased on other physiological patterns and adjust the blood glucosetargets for that individual based on the specific day of the week orbased on other physiological patterns. For example, a PWD may havecertain days of the week when they exercise and/or PWD may havedifferent insulin needs based on a menses cycle.

Methods and systems provided herein can evaluate each basal insulindelivery profile or rate to select the profile or rate that minimizes avariation from the one or more blood glucose targets using anyappropriate method. In some cases, methods and systems provided hereincan use a cost function to evaluate differences between the predictedblood glucose values for each basal insulin delivery profile or rate andblood glucose targets, potentially specified for a diurnal time segment.Methods and systems provided herein can then select a basal profile orrate that produces the lowest cost function value. Methods and systemsprovided herein can use any suitable cost function. In some cases, costfunctions can sum the absolute value of the difference between eachpredicted blood glucose value and each blood glucose target. In somecases, cost functions used in methods and systems provided herein canuse square of the difference. In some cases, cost functions used inmethods and systems provided herein can assign a higher cost to bloodglucose values below the blood glucose target in order reduce the riskof a hypoglycemic event. In some cases, the cost function can include asummation of the absolute values of a plurality of predicted deviations,squared deviations, log squared deviations, or a combination thereof. Insome cases, a cost function can include variables unrelated to thepredicted blood glucose values. For example, a cost function can includea penalty for profiles that do not deliver 100% of the BBR, thus addinga slight preference to use 100% of BBR. In some cases, methods andsystems provided herein can include a cost function that provides aslight preference to keep the existing basal modification for everyother interval (e.g., a second 15 minute segment), which could reducethe variability in basal insulin delivery rates in typical situations,but allow for more critical adjustments.

Methods and systems provided herein can receive various inputs from auser related to the delivery of basal insulin. In some cases, a user mayinput a fear of hypoglycemia (FHI) index. The FHI may indicate thepreference for or reticence to experience certain blood glucose levelsby the PWD. For example, the FHI may indicate that the PWD prefers“high” blood glucose levels (e.g., blood glucose levels above athreshold); or as another example, the FHI may indicate that the PWD isconcerned about “going low” (e.g., blood glucose levels below athreshold). In some cases, the FHI may correspond to a threshold and anacceptable probability of crossing the threshold, including using thethreshold to signify going high or using the threshold to signify goinglow, or both. In some cases, a probability of the PWD crossing thethreshold may be determined and a baseline basal insulin rate may bemodified to more closely align the acceptable probability of crossingthe threshold with the actual probability of crossing the threshold.Additionally or alternatively, the FHI may be used in other ways inmethods and systems of the present disclosure. For example, modificationof the baseline basal insulin rate for a diurnal period may be modifiedone way for a high FHI and another way for a low FHI. As anotherexample, multiple profiles of insulin delivery steps may use one set ofpossible steps for a high FHI, and another set of possible steps for alow FHI.

Methods and systems provided herein can modify or alter an insulindelivery profile or rate in any number of ways. In some cases, a usermay select a temporary override to indicate a user preference for aparticular blood glucose level. For example, the PWD may indicate thatthey are going for a long drive and do not want to have their bloodglucose levels drop below a certain level, and so may designate a targetblood glucose level higher than their normal target blood glucose level,which may be set for a particular or indefinite length of time. In somecases, methods and systems provided herein may modify or otherwiseselect a new profile or rate from multiple profiles that corresponds tothe blood glucose level from the temporary override. In some cases,methods and systems provided herein can permit a user to merely indicatea reduced tolerance for the risk of going low and can determine atemporary blood glucose level based on the variability of blood glucosedata for that PWD for previous days (optionally for a particular diurnaltime segment).

Methods and systems provided herein can store a plurality ofuser-specific dosage parameters (e.g., BBR, CR, and ISF) as differentvalues for a plurality of different diurnal time segments. As usedherein, “diurnal time segments” periods of time during each day, suchthat the methods and systems will repeat use of each diurnal-specificuser-specific dosage parameter during the same time on subsequent daysif a stored diurnal-specific user-specific dosage parameter is notmodified or change, thus the use of the stored diurnal-specificuser-specific dosage parameter will wrap each day. Methods and systemsprovided herein, however, can be adapted to make daily (or more or lessfrequent) adjustments to each diurnal-specific user-specific dosageparameter based on the operation of the system. Methods and systemsprovided herein may additionally store settings or adjustments forspecific days of the week or for other repeating cycles.

After a basal insulin delivery profile or rate is selected, methods andsystems provided herein can include the delivery of basal insulin to thePWD according to the selected basal insulin profile or rate for anysuitable period of time. In some cases, methods and systems providedherein may supply basal insulin according to the selected basal insulindelivery profile or rate for a predetermined amount of time that may beless than the time interval of the evaluated basal insulin deliveryprofiles or rates. For example, methods and systems provided herein mayanalyze projected blood glucose values for basal insulin deliveryprofiles or rates that last over the next four hours but repeat theprocess of selecting a new basal insulin delivery profile or rate everyfifteen minutes. In some cases, methods and systems provided herein candelay or suspend basal insulin delivery during the delivery of a bolus,which can be triggered by a user requesting a bolus.

As used herein, “basal insulin delivery” has its normal and customarymeaning within the art of the treatment of diabetes. Although basalrates are expressed as a continuous supply of insulin over time, basalinsulin delivery may constitute multiple discrete deliveries of insulinat regular or irregular intervals. In some cases, methods and systemsprovided herein may only be able to deliver insulin in discretefractions of a unit. For example, some insulin delivery devices can onlydeliver insulin in a dose that are an integer multiple of 0.05 unit or0.1 unit. In some cases, a delivery of basal insulin can include adelivery of insulin at predetermined time intervals less than or equalto fifteen minutes apart or less, ten minutes apart or less, or fiveminutes apart or less. In some cases, the time interval between discretebasal insulin deliveries can be determined based on the basal insulindelivery rate (e.g., a basal rate of 1.0 unit/hour might result in thedelivery of 0.1 unit every six minutes). As used herein, the term“bolus” has its normal and customary meaning with the art of thetreatment of diabetes, and can refer to a bolus delivered in order tocounteract a meal (i.e., a meal-time bolus) and/or to correct forelevated blood glucose levels (i.e., a correction bolus).

Methods and systems provided herein can in some cases include multipledelivery modes. In some cases, methods and systems provided herein canmonitor the presence of blood glucose using one or more blood glucosemeasuring devices or methods, control or monitor the dispensation ofmedicine, and determine and/or update the user-specific dosageparameters regardless of the operating mode. For example, possibleoperating modes could include closed-loop or hybrid closed-loop modesthat automatically adjust basal rates based on continuous glucosemonitoring data (CGM) and other user-specific dosage parameters (e.g.,baseline basal rate (BBR), insulin sensitivity factor (ISF), andcarbohydrate-to-insulin ratio (CR)), modes that can use blood glucosemonitor (BGM) data to update user-specific dosage parameters (e.g.,BBRs, ISFs, and CRs) for different time blocks over longer periods oftime, manual modes that require a patient to manually control thetherapy program using an insulin pump, and advisory modes that recommenddosages for a PWD to inject using an insulin pen or syringe. Bydetermining optimized control parameters that work across deliverymodes, systems and methods provided herein can provide superior analytecontrol even when a PWD switches to a different delivery mode. Forexample, methods and systems provided herein may be forced to switchaway from a hybrid closed-loop delivery mode that adjusts basal insulindelivery away from a BBR if a continuous glucose monitor malfunctions orthe system otherwise loses access to continuous data. In some cases,data can be collected when the system is in an advisory or manual modeto optimize control parameters in preparation for a PWD to switch to ahybrid closed-loop system (e.g., in preparation for a PWD to start useof a continuous glucose monitor (CGM) and/or an insulin pump).

Methods and systems provided herein can include an insulin pump and atleast one blood glucose measurement device in communication with theinsulin pump. In some cases, the blood glucose measurement device can bea CGM adapted to provide blood glucose measurements at least everyfifteen minutes. In some cases, methods and systems provided hereininclude a CGM adapted to provide blood glucose measurements at leastevery ten minutes. In some cases, methods and systems provided hereininclude a CGM adapted to provide blood glucose measurements every fiveminutes. Methods and systems provided herein additionally include acontroller adapted to determine an amount of basal insulin for deliveryto a PWD and memory to store multiple user-specific dosage parameters.In some cases, the controller can be part of an insulin pump. In somecases, a controller can be part of a remote device, which cancommunicate wirelessly with an insulin pump. In some cases, thecontroller can communicate wirelessly with a CGM. In some cases, methodsand systems provided herein can additionally include a user interfacefor displaying data and/or receiving user commands, which can beincluded on any component of a system provided herein. In some cases,the user interface can be part of a smartphone. In some cases, a usercan input information on the user interface to trigger methods andsystems provided herein to deliver a bolus of insulin. In some cases,methods and systems provided herein can use a blood glucose meteradapted to use test strip as a blood glucose measurement device. In somecases, methods and systems provided herein can additionally include aninsulin pen, which can optionally communicate wirelessly with acontroller.

Example Diabetes Management System

FIG. 1 depicts an example diabetes management system 10 including a pumpassembly 15 for insulin and a continuous glucose monitor (CGM) 50. Asshown, the continuous glucose monitor 50 is in wireless communicationwith pump assembly 15. In some cases, a continuous glucose monitor canbe in wired communication with pump assembly 15. In some cases, notshown, a continuous glucose monitor can be incorporated into an insulinpump assembly. As shown, pump assembly 15 can include a reusable pumpcontroller 200 that forms part of the pump assembly 15. In some cases,reusable pump controller 200 is adapted to determine one or more basaldelivery rates. In some cases, continuous glucose monitor 50 can act asa controller adapted to communicate basal delivery rates to pumpassembly 15.

Pump assembly 15, as shown, can include reusable pump controller 200 anda disposable pump 100, which can contain a reservoir for retaininginsulin. A drive system for pushing insulin out of the reservoir can beincluded in either the disposable pump 100 or the reusable pumpcontroller 200 in a controller housing 210. Reusable pump controller 200can include a wireless communication device 247, which can be adapted tocommunicate with a wireless communication device 54 of continuousglucose monitor 50 and other diabetes devices in the system, such asthose discussed below. In some cases, pump assembly 15 can be sized tofit within a palm of a hand 5. Pump assembly 15 can include an infusionset 146. Infusion set 146 can include a flexible tube 147 that extendsfrom the disposable pump 100 to a subcutaneous cannula 149 that may beretained by a skin adhesive patch (not shown) that secures thesubcutaneous cannula 149 to the infusion site. The skin adhesive patchcan retain the cannula 149 in fluid communication with the tissue orvasculature of the PWD so that the medicine dispensed through tube 147passes through the cannula 149 and into the PWD's body. A cap device 130can provide fluid communication between an output end of an insulincartridge (not shown) and tube 147 of infusion set 146. Although pumpassembly 15 is depicted as a two-part insulin pump, one piece insulinpumps are also contemplated. Additionally, insulin pump assemblies usedin methods and systems provided herein can alternatively be a patchpump.

Continuous glucose monitor 50 (e.g., a glucose sensor) can include ahousing 52, a wireless communication device 54, and a sensor shaft 56.The wireless communication device 54 can be contained within the housing52 and the sensor shaft 56 can extend outward from the housing 52. Inuse, the sensor shaft 56 can penetrate the skin 20 of a user to makemeasurements indicative of the PWD's blood glucose level or the like. Insome cases, the sensor shaft 56 can measure glucose or another analytein interstitial fluid or in another fluid and correlate that to bloodglucose levels. In response to the measurements made by the sensor shaft56, the continuous glucose monitor 50 can employ the wirelesscommunication device 54 to transmit data to a corresponding wirelesscommunication device 247 housed in the pump assembly 15. In some cases,the continuous glucose monitor 50 may include a circuit that permitssensor signals (e.g., data from the sensor shaft 56) to be communicatedto the wireless communication device 54. The wireless communicationdevice 54 can transfer the collected data to reusable pump controller200 (e.g., by wireless communication to the wireless communicationdevice 247). Additionally or alternatively, the system 10 may includeanother glucose monitoring device that may utilize any of a variety ofmethods of obtaining information indicative of a PWD's blood glucoselevels and transferring that information to reusable pump controller200. For example, an alternative monitoring device may employ amicropore system in which a laser porator creates tiny holes in theuppermost layer of a PWD's skin, through which interstitial glucose ismeasured using a patch. In the alternative, the monitoring device canuse iontophoretic methods to non-invasively extract interstitial glucosefor measurement. In other examples, the monitoring device can includenon-invasive detection systems that employ near IR, ultrasound orspectroscopy, and particular implementations of glucose-sensing contactlenses. In other examples, the monitoring device can include detectglucose levels using equilibrium fluorescence detectors (e.g., sensorsincluding a diboronic acid receptor attached to a fluorophore).Furthermore, it should be understood that in some alternativeimplementations, continuous glucose monitor 50 can be in communicationwith reusable pump controller 200 or another computing device via awired connection. In some cases, continuous glucose monitor 50 can beadapted to provide blood glucose measurements for a PWD when in use forthe PWD at regular or irregular time intervals. In some cases,continuous glucose monitor 50 can detect blood glucose measurements atleast every thirty minutes, at least every fifteen minutes, at leastevery ten minutes, at least every five minutes, or about every minute.In some cases, continuous glucose monitor 50 can itself determine abasal delivery rate using methods provided herein and communicate thatbasal rate to the pump assembly 15. In some cases, continuous glucosemonitor 50 can transmit blood glucose measurement data to reusable pumpcontroller 200 and reusable pump controller 200 can use methods providedherein to determine a basal delivery rate. In some cases, a remotecontroller can receive glucose data from continuous glucose monitor 50,determine a basal delivery rate using methods provided herein, andcommunicate the basal rate to pump assembly 15.

Diabetes management system 10 may optionally include a blood glucosemeter (BGM) 70 (e.g., a glucose sensor). In some cases, blood glucosemeter 70 can be in wireless communication with reusable pump controller200. Blood glucose meter 70 can take a blood glucose measurement usingone or more test strips (e.g., blood test strips). A test strip can beinserted into a strip reader portion of the blood glucose meter 70 andthen receive the PWD's blood to determine a blood glucose level for thePWD. In some cases, the blood glucose meter 70 is configured to analyzethe characteristics of the PWD's blood and communicate (e.g., via aBLUETOOTH® wireless communication connection) the information toreusable pump controller 200. In some cases, a user can manually input aglucose meter reading. The blood glucose meter 70 can be manuallyoperated by a user and may include an output subsystem (e.g., display,speaker) that can provide the user with blood glucose readings that canbe subsequently entered into the controller or user interface to collectthe data from an unconnected BGM into the system. The blood glucosemeter 70 may be configured to communicate data (e.g., blood glucosereadings) obtained to reusable pump controller 200 and/or other devices,such as a mobile computing device 60 (e.g., a control device). Suchcommunication can be over a wired and/or wireless connection, and thedata can be used by system 10 for a number of functions (e.g.,calibrating the continuous glucose monitor 50, confirming a reading fromthe continuous glucose monitor 50, determining a more accurate bloodglucose reading for a bolus calculation, detecting a blood glucose levelwhen the continuous glucose monitor 50 is malfunctioning).

In some cases, the system 10 can further include a mobile computingdevice 60 that can communicate with the reusable pump controller 200through a wireless and/or wired connection with the reusable pumpcontroller 200 (e.g., via a BLUETOOTH® wireless communication connectionor a near-field communication connection). In some cases, the mobilecomputing device 60 communicates wirelessly with other diabetes devicesof system 10. The mobile computing device 60 can be any of a variety ofappropriate computing devices, such as a smartphone, a tablet computingdevice, a wearable computing device, a smartwatch, a fitness tracker, alaptop computer, a desktop computer, and/or other appropriate computingdevices. In some cases (for example, where the reusable pump controller200 does not determine a basal delivery rate), the mobile computingdevice 60 can receive and log data from other elements of the system 10and determine basal delivery rates using methods provided herein. Insome cases, a user can input relevant data into the mobile computingdevice 60. In some cases, the mobile computing device 60 can be used totransfer data from the reusable pump controller 200 to another computingdevice (e.g., a back-end server or cloud-based device). In some cases,one or more methods provided herein can be performed or partiallyperformed by the other computing device. In some cases, the mobilecomputing device 60 provides a user interface (e.g., graphical userinterface (GUI), speech-based user interface, motion-controlled userinterface) through which users can provide information to controloperation of the reusable pump controller 200 and the system 10. Forexample, the mobile computing device 60 can be a mobile computing devicerunning a mobile app that communicates with reusable pump controller 200over short-range wireless connections (e.g., BLUETOOTH® connection,Wi-Fi Direct connection, near-field communication connection, etc.) toprovide status information for the system 10 and allow a user to controloperation of the system 10 (e.g., toggle between delivery modes, adjustsettings, log food intake, change a fear of hypoglycemia index (FHI),confirm/modify/cancel bolus dosages, and the like).

Optionally, system 10 may include a bolus administering device 80 (e.g.,a syringe, an insulin pen, a smart syringe with device communicationcapabilities, or the like) through which bolus dosages can be manuallyadministered to a PWD. In some cases, a suggested dosage for a bolus tobe administered using the bolus administering device 80 can be output toa user via the user interface of reusable pump controller 200 and/or theuser interface of the mobile computing device 60. In some cases, thebolus administering device 80 can communicate through a wired and/orwireless connection with reusable pump controller 200 and/or the mobilecomputing device 60. In some cases, system 10 can allow users to inputinsulin deliveries made using a syringe or insulin pen.

Operation of a Diabetes Management System

FIG. 2 depicts an example method 202 for operation of a diabetesmanagement system, such as system 10 depicted in FIG. 1. As shown inFIG. 2, a system can receive user inputs, such as user inputs at blocks251 and 252, which can be used to provide initial settings, such as oneor more target blood glucose values that may be used or determined atblock 261 and/or one or more user-specific dosage parameters that may beused or determined at block 262. In some cases, user inputs at blocks251 and 252 can be entered by a PWD, a caregiver for the PWD, or ahealthcare professional. In some cases, user inputs at blocks 251 and252 can be entered on a mobile computing device 60, such as asmartphone. Based on the user-specific dosage parameters, the method 202can generate multiple basal insulin delivery profiles and/or rates atblock 263. In some cases, the plurality of basal insulin deliveryprofiles and/or rates can be based upon one or more baseline basalrates. At block 264, the method 202 can analyze each basal deliveryprofile or rate generated at block 263 based on variations of predictedfuture blood glucose values from one or more target blood glucose values(such as the target blood glucose values from block 261) using bloodglucose data from a continuous glucose monitor (CGM) or blood glucosemeter (BGM), such as generated in block 271. In some cases, the bloodglucose data can be from the continuous glucose monitor 50 from thesystem 10 of FIG. 1. As will be discussed below, predicted blood glucosevalues for each generated basal delivery profile or rate can useuser-specific dosage parameters (for example, those determined orotherwise adjusted at block 262). Additionally, predicted blood glucosevalues can include inputs regarding previous dosages of insulin and/orfood consumption (e.g., estimates of carbohydrates consumed). In somecases, predicted blood glucose values used at block 264 can considerdata indicative of exercise, sickness, or any other physical state thatmight impact blood glucose levels in a PWD. Based on an analysis of avariation of predicted blood glucose levels performed at block 264, abasal delivery profile or rate generated at block 263 can be selected atblock 265, and the system can deliver basal insulin according to thatselected basal delivery profile or rate to the PWD for a select periodof time at block 272. In some cases, the pump assembly 15 of system 10of FIG. 1 can be used to deliver the insulin. In some cases, the blocks263, 264, 265, and 272 can each be conducted by reusable pump controller200 of system 10. In some cases, the blocks 271, 263, 264, and 265 canall be conducted by continuous glucose monitor 50 of system 10, withdata regarding the selected delivery rate being sent to reusable pumpcontroller 200. In some cases, the blocks 251, 252, 261, 262, 263, 264,and 265 can all be conducted on mobile computing device 60 of system 10of FIG. 1, with data regarding the selected delivery rate being sent toreusable pump controller 200 from the mobile computing device 60.

Methods and systems provided herein can additionally update or adjustuser-specific dosage parameters at block 262 and can update or adjustthe blood glucose targets at block 261 based on the selected basaldelivery profiles and/or rates selected at block 265 or based on bloodglucose data obtained at block 271. In some cases, at block 281, periodsof time when a selected basal delivery was different from baseline basalrate for that period of time can be detected. For these select periodsof time (e.g., diurnal time segments), at block 262 the user-specificdosage parameters can be adjusted for that period of time. For example,if the selected basal delivery for a time block exceeds the baselinebasal rate for that time block, at block 262 the system 10 can increasethe baseline basal rate for that time block (e.g., a diurnal period) orsome other related time block (such as the preceding diurnal period).For example, if the selected basal delivery from 2 PM to 3 PM exceededthe baseline basal rate for that time, the system 10 may increase thebaseline basal rate for 2 PM to 3 PM or may adjust the baseline basalrate for 1 PM to 2 PM, 12 PM to 1 PM and/or 11 AM to 12 PM. In somecases, each adjustment to a baseline basal rate is less than thedifference between the baseline basal rate and the selected basaldelivery. In some cases, each adjustment can be a predetermined amount(e.g., baseline basal rate adjusted up or down by 0.5 unit/hour, 0.3unit/hour, 0.1 unit per hour) or percentage (e.g., 5%, 3%, 1%), whichcan limit the change to the user-specific dosage parameters due to anirregular event. At block 283, the variability of blood glucose data canbe analyzed to make adjustments to the blood glucose target(s) at block261. For example, at block 283, a blood glucose data distribution can bedetermined for a diurnal period (e.g., between 1 AM and 2 AM) todetermine a measure of dispersion of blood glucose values for the PWDduring that diurnal period, and at block 261 adjustments can be made tothe blood glucose target for that diurnal period, and/or adjacentperiods, based on the measure of dispersion.

Each of the processes discussed in regards to FIG. 2 are discussed atfurther length below.

Setting Initial User-Specific Dosage Parameters

Systems and methods provided herein can use multiple user-specificdosage parameters for a PWD in order to determine rates of basal insulindelivery and optionally amounts of bolus insulin delivery. In somecases, initial user-specific dosage parameters can be set by ahealthcare professional. In some cases, data entered by a user (e.g.,the PWD, the PWD's caregiver, or a health care professional) can be usedto estimate one or more user-specific dosage parameters. For example,FIG. 2 depicts a method where a user enters at least one dosageparameter at block 252.

In some cases, multiple user-specific dosage parameters can be set formultiple diurnal time segments. In some cases, different user-specificdosage parameters can have diurnal time segments of the same length oftime or different lengths of time. In some cases, an initial setting foreach user-specific dosage parameter can be set at the same value foreach diurnal time segment, but the user-specific dosage parameter foreach diurnal time segment can be independently adjusted in the methodsand systems provided herein. In some cases, users (e.g., health careprofessionals) can input different user-specific dosage parameter valuesfor different diurnal time segments.

Methods and systems provided herein can, in some cases, useuser-specific dosage parameters that are commonly used in the treatmentof diabetes. For example, methods and systems provided herein can ask auser to input one or more of an average Total Daily Dose (TDD) ofinsulin, a total daily basal (TDB) dose of insulin, an average basalrate (ABR) (which can be used as an initial baseline basal rate (BBR) inmethods and systems provided herein), an insulin sensitivity factor(ISF), and/or a carbohydrate-to-insulin ratio (CR). In some cases,methods and systems provided herein can ask for a weight, age, orcombination thereof of a PWD to estimate one or more user-specificdosage parameters. In some cases, methods and systems will store a BBR,an ISF, and a CR, which can each be set for multiple different timeblocks over a repeating period of time (e.g., fifteen, thirty, sixty, orone hundred and twenty minute diurnal periods). As will be discussed infurther detail below, methods and systems provided herein can adjustuser-specific dosage parameters for each of the diurnal periods in orderto personalize the delivery of insulin for the PWD in order to minimizerisks for the PWD.

Methods and systems provided herein can ask for or permit a user toinput a variety of different user-specific dosage parameters or dosageproxies to determine values for the initial settings of one or moreuser-specific dosage parameters and/or blood glucose targets. In somecases, the inputs can be limited to a Total Daily Basal (TDB) amount ofinsulin and a Fear of Hypoglycemia Index (FHI). In some cases, theinputs can be limited to a Total Daily Dose (TDD) amount of insulin anda FHI. In some cases, the TDB or TDD can be used determine the initialbaseline basal rate (BBR), the initial carbohydrate-to-insulin ratio(CR), and the initial insulin sensitivity factor (ISF) based onmathematical relationships among and between for BBR, CR, ISF, TDB, andTDD. In some cases, a user can also set an initial ISF and CR. In somecases, a user (e.g., a health care professional) can optionally inputany combination of BBR, CR, ISF, TDB, and TDD, and at least the initialBBR, initial CR, and initial ISF can be based on the values entered. Forexample, in some cases, a relationship between initial TDB, TDD, BBR,CR, and ISF can be expressed as follows: TDD [u/day]=2×TDB[u/day]=1800/ISF [mg/dL/u or [mmol/u]=400/CR [g/u]=48 hours/day×BBR[u/hour]. In some cases, the mathematical equation used to estimate ISF,CR, and BBR can use non-linear relationships between BBR, ISF, and CR.

Methods and systems provided herein can also make adjustments touser-entered user-specific dosage parameters prior to initial use. Insome cases, methods and systems provided herein adjust user enteredinitial BBR, CR, and/or ISF values based on mathematical relationshipsamong and between the initial BBR, CR, and ISF values. In some cases, ifan entered ISF and an entered CR are outside of a predefinedrelationship between BBR, CR, and ISF, methods and systems providedherein will calculate a CR and an ISF that meets a predeterminedrelationship between BBR, CR, and ISF while minimizing a total changefrom the entered values for ISF and CR. In some cases, the predeterminedrelationship permits a range of CR values for each ISF value, permits arange of ISF values for each CR value, and permits a range of ISF and CRvalues for each BBR value. In some cases, the predetermined relationshiprepresents a confidence interval for empirical data regardingrelationships between basal rates, ISF, and CR values for a populationof PWDs. In some cases, if an entered ISF, BBR, and/or CR are outside ofa predefined relationship between BBR, CR, and ISF, methods and systemsof the present disclosure may notify the user of the deviation from thepredefined relationship. Additionally or alternatively, a healthcareprovider override may be required to include ISF, BBR, and/or CR valuesoutside of the predefined relationship as the initial user-specificdosage parameters.

Setting Initial Blood Glucose Targets

Initial blood glucose targets can be set or determined using anysuitable technique. In some cases, blood glucose targets can bepreprogrammed on memory within a system or device provided herein. Insome cases, there can be a single blood glucose target preprogrammedinto the system that does not change. In some cases, the diurnal timesegments can each have a preprogrammed blood glucose target. In somecases, a user can program one or more blood glucose targets, which canbe set differently for different periods of time. In some cases, a usercan program the typical sleeping schedule, exercise schedule, and/ormeal schedule for a PWD, and methods and systems provided herein canselect lower blood glucose targets for sleep times and higher bloodglucose targets around meal times and/or exercise times. In some cases,historical continuous glucose monitor data for the PWD prior to the PWDusing the system can be used to set initial blood glucose targets(either for specific diurnal periods or for an entire day). In somecases, methods provided herein can have a PWD wear a CGM for apreliminary period of time (e.g., at least twenty-four hours, at leastforty-eight hours, at least five days, or at least ten days) prior toallowing the methods and systems provided herein from delivering insulinat rates other than the BBR to detect blood glucose variability data forthe PWD to set one or more initial blood glucose targets.

In some cases, such as shown in FIG. 2 at block 251, a user can enter afear of hypoglycemia index (FHI), which can be used to determine and/oradjust blood glucose targets. An FHI can be represented to the user in anumber of ways. In some cases, the FHI can be represented to the user asan aggressiveness index, which could be set at “prefer high,” “preferlow,” or “prefer moderate.” In some cases, the FHI can be represented tothe user as a target blood glucose level or target average blood glucoselevel (e.g., 100 mg/dl, 120 mg/dl, or 140 mg/dl). In some cases, the FHIcan be represented to the user as a target A1C level. In some cases, theFHI can be represented to the user as a probability of going above orbelow a certain threshold (e.g., a five percent chance of going below 80mg/dl, or a three percent chance of going above 200 mg/dl). In these andother cases, a user interface may be generated with an interactivefeature (e.g., radio buttons, check boxes, hyperlinked images/text,drop-down list, etc.) that a user can interact with to make a selectionof the FHI. In some cases, the PWD may interact with the interface toselect the FHI, and in some cases, the user can be a health careprofessional that selects the FHI.

In some cases, each possible FHI value can correspond to a preprogrammedinitial blood glucose target. For example, an FHI of “prefer high” mightcorrespond to a preprogrammed initial blood glucose target of 140 mg/dl,an FHI of “prefer moderate” might correspond to a preprogrammed initialblood glucose target of 120 mg/dl, and an FHI of “prefer low” mightcorrespond to a preprogrammed initial blood glucose target of 100 mg/dl.As will be discussed below, initial blood glucose targets can beadjusted over time based on data collected in methods and systemsprovided herein.

Modes of Operation

Methods and systems provided herein can in some cases include multipledelivery modes. In some cases, methods and systems provided herein canmonitor the presence of blood glucose using one or more blood glucosemeasuring devices or methods, control or monitor the dispensation ofinsulin, and determine and/or update the user-specific dosage parametersregardless of the operating mode. For example, possible operating modescould include closed-loop or hybrid closed-loop modes that automaticallyadjust basal rates based on continuous glucose monitoring data (CGM) andother user-specific dosage parameters (e.g., BBR, ISF, and CR), modesthat can use blood glucose monitor (BGM) data to update user-specificdosage parameters (e.g., BBRs, ISFs, and CRs) for different time blocksover longer periods of time, manual modes that require a patient tomanually control the therapy program using an insulin pump, and advisorymodes that recommend dosages for a user to inject using an insulin penor syringe. By determining optimized control parameters that work acrossdelivery modes, systems and methods provided herein can provide superiorblood glucose control even when a PWD switches to a different deliverymode. For example, methods and systems provided herein may be forced toswitch away from a hybrid closed-loop delivery mode that adjusts basalinsulin delivery away from a BBR if a continuous glucose monitormalfunctions or the system otherwise loses access to continuous data,yet still use a personalized ISF and CR for calculating correctionand/or mealtime bolus amounts. In some cases, data can be collected whenthe system is in an advisory or manual mode to optimize controlparameters in preparation for a PWD to switch to a hybrid closed-loopsystem (e.g., in preparation for a PWD to start use of a continuousglucose monitor (CGM) and/or an insulin pump). In some cases, the use ofa closed-loop delivery mode that adjusts basal insulin delivery awayfrom a BBR may be prevented until a sufficient amount of current bloodglucose data is available (e.g., the insulin delivery according tomultiple profiles that can occur at blocks 263, 264, 265, and 272 ofFIG. 2 may not occur until sufficient CGM and/or BGM data is collectedat the block 271 of FIG. 2). In some cases, systems and methods providedherein can deliver insulin at the BBR rate for each diurnal period wheninsufficient blood glucose data is available. In some cases, methods andsystems provided herein can switch between open loop and closed-loopmodes based on whether there are a predetermined number of authenticatedblood glucose measurements from a continuous glucose monitor within apredetermined period of time (e.g., at least two authenticated bloodglucose data points within the last twenty minutes).

Automating Basal Insulin Delivery

Systems and methods provided herein can automate basal insulin deliverybased on one or more stored user-specific dosage parameters (e.g., BBR,ISF, CR), one or more blood glucose targets, and/or blood glucose data.The example method depicted in FIG. 2 depicts an example process ofautomating basal insulin delivery as blocks 263, 264, 265, and 272.Methods and systems provided herein can use a model predictive controlsystem that projects multiple future blood glucose levels for a futuretime period for multiple possible basal insulin delivery profiles and/orrates over that future time period and determines which of the multiplepossible basal insulin delivery profiles and/or rates will producefuture blood glucose values that approximate one or more blood glucosetargets. Methods and systems provided herein can produce improvedcontrol as compared to control algorithms that merely make adjustmentsto basal insulin delivery without evaluating multiple possible basalinsulin delivery profiles or rates. In some cases, methods and systemsprovided herein can predict future blood glucose values at least twohours, or at least three hours, or at least four hours, or at least fivehours into the future, which can adequately consider the long termimpact of increasing or decreasing the basal insulin delivery relativeto the BBR. After a rate or profile is selected, the rate or profile canbe delivered for a predetermined delivery period of time (for example,the block 272 of FIG. 2) prior to repeating one or more of the steps inthe process of selecting a new basal insulin delivery profile or rate.In some cases, this predetermined delivery period of time can be lessthan the length of time for the generated basal insulin deliveryprofiles and/or rates and less than the time period for which futureblood glucose values were estimated, thus methods and systems providedherein can dynamically make changes to basal insulin delivery based onrecent blood glucose data. For example, generating basal deliveryprofiles at block 263 may be repeated every fifteen minutes, and theperiod of time evaluated at block 264 may be a four hour window suchthat every fifteen minutes, a new four hour window of analysis for thebasal delivery profiles is generated. In this way, each delivery actionis based on a prediction not only of that action, but on how the priordelivery action is determined to impact blood glucose levels for fourhours into the future.

Generating Possible Basal Delivery Profiles and/or Rates for Evaluation

FIG. 3 illustrates an example chart 300 of delivery profiles 310 a-310 qover a four hour time horizon. FIG. 3 also includes a graph 320illustrating the projected effect of the profiles 310 a-310 q on bloodglucose levels, and a graph 330 illustrating an accumulation ofvariations from a target blood glucose level (e.g., loss) using a costfunction.

Possible basal insulin delivery profiles and/or rates can be generatedusing any suitable technique. In some cases, each generated profile orrate can be based on user-specific dosage parameters. In some cases,each generated profile or rate can be based on one or more user-specificdosage parameters that are specific to a particular diurnal period. Insome cases, each generated profile or rate is based on a predeterminedrelationship to a stored baseline basal rate (BBR), such as indicated atblock 263 in FIG. 2. In some cases, generated profiles and/or rates foranalysis extend for at least two hours, at least three hours, or for atleast four hours. In some cases, the generated profiles may extend for aday (e.g., twenty-four hours) or less. In some cases, each generatedprofile or rate includes basal insulin delivery rates based onpredetermined multiples or fractions of one or more stored BBRs. In somecases, multiple insulin delivery profiles and/or rates are based onmultiple diurnal-time-block-specific BBRs. In some cases, generatedbasal insulin delivery profiles each deliver insulin at a ratio of aBBR, such as an integer multiple of one or more stored BBRs (e.g.,0×BBR, 1×BBR, 2×BBR, and 3×BBR). In some cases, insulin deliveryprofiles can delivery insulin at ratios that may include both fractionsand multiples of one or more stored BBRs (e.g., 0×BBR, 0.5×BBR, 1×BBR,1.5×BBR, and 2×BBR). In some cases, generated basal insulin deliveryprofiles each deliver insulin at only multiples or fractions of between0 and 3. In some cases, generated basal insulin delivery profiles eachdeliver insulin at only multiples or fractions of between 0 and 2. Insome cases, such as shown in FIG. 3, multiple generated basal deliveryprofiles can include only deliveries of basal insulin at 0% of BBR, 100%of BBR, or 200% of BBR. In some cases, each generated basal deliveryprofile permutation has fixed future time periods. In some cases,different future time periods for permutations can have differentlengths. In some cases, the number of generated basal delivery profilesor rates for evaluation is less than 100, less than 50, less than 30,less than 25, or less than 20. By limiting the number of evaluatedpreset permutations based on stored BBRs, methods and systems providedherein can limit an energy expenditure used to run a controllerdetermining a basal delivery rate.

In some cases, one or more of the profiles 310 a-310 q may include aninflection point between a first insulin delivery amount for a firstportion of delivery actions and a second delivery amount for a secondportion of delivery actions. For example, the profile 310 b may includean inflection point between 0% and 100% between 3.5 hours and 4 hours(e.g., for the portion before the inflection point, 0% of the BBR isdelivered as the delivery action and for the portion after theinflection point, 100% of the BBR is delivered as the delivery action).As another example, the profile 310 k may include an inflection pointbetween 100% and 200% between 1 hour and 1.5 hours (e.g., before theinflection point, 100% of the BBR is delivered as the delivery actionand after the inflection point, 200% of the BBR is delivered as thedelivery action). In some cases, such as illustrated in FIG. 3, eachprofile may be a permutation of including one inflection point (or noinflection point) between three possible delivery actions (e.g., 0%,100%, 200%), yielding seventeen profiles for a four hour window ofprojection. In some cases, more than one inflection point may be used,yielding additional profiles. In some cases, the number of profiles maybe fewer than thirty. In some cases, only three profiles are analyzed(e.g., profiles 8, 9, and 10 of FIG. 3, 310 h-j) in order to selectbetween whether to delivery 0%, 100%, or 200%. In some cases, theinclusion of additional profiles assuming no basal insulin (e.g.,profile 1, 310 a) or continuing supply of maximum basal insulin (e.g.,17, 310 q) can allow the system to detect an approaching predictedhypoglycemic event or an approaching predicted hyperglycemic event, andadditional profiles (e.g., 2-7 & 11-16) can be selected and recorded todetect situations where future decisions are not conforming to anexpected profile. In some cases, methods and systems provided herein cancontinue to deliver insulin according to a selected profile after theselect period of time in block 272, including changes in basal deliveryrates, if reliable up-to-date blood glucose data is lost. In othercases, methods and systems provided herein will revert to another modeor alarm and stop insulin delivery if reliable up-to-date blood glucosedata is lost.

In some cases, the range of possible values of the BBR for a givenprofile can be adjusted or modified depending on the FHI. For example,in some cases, if the FHI is “prefer low” (e.g., indicating a preferencefor the system to aggressively keep the PWD within range and not gohigh), the target blood glucose might be set around 100 mg/dl and therange for delivery may include 0%, 50%, 100%, 200%, and 300% BBR. Asanother example, if the FHI is “prefer high” (e.g., indicating that thePWD prefers to avoid hypoglycemic events even with a higher risk ofhyperglycemic events), the target blood glucose might be set around 140mg/dl and the range for delivery may include 0%, 100%, and 200% of BBR.

Evaluating Generated Basal Delivery Profiles and/or Rates

Referring again to FIG. 2 and FIG. 3, the evaluation of multiplegenerated basal insulin delivery profiles and/or rates includesprojecting future blood glucose levels and comparing those to bloodglucose targets. In some cases, multiple permutations may be generatedand analyzed. FIG. 3 depicts possible projections for each permutationof insulin delivery depicted in FIG. 3.

Predicting Future Blood Glucose Values

Systems and methods provided herein can use any suitable physiologymodel to predict future blood glucose values. In some cases, methods andsystems provided herein can predict future blood glucose values usingpast and current carbohydrate, insulin, and blood glucose values.

Systems and methods provided herein can in some cases estimate a firstfuture blood glucose a model as depicted in FIG. 4. In some cases, bloodglucose can be approximated using two determinist Integrating firstorder plus dead time (FOPDT) models for the effect of carbohydrates andinsulin, combined with an autoregressive (AR2) disturbance model.Accordingly, blood glucose (BG) at time (t) can be estimated using thefollowing equation:BG _(t) =y _(t) =BGc _(t) +BGi _(t) +BGd _(t) =G _(c) c _(t) +G _(i) i_(t) +G _(d) e ^(a) ^(t)

From the equation above, the first element may represent the effect onblood glucose due to carbohydrates:

$G_{c} = {\frac{{K_{c}\left( {1 - \alpha_{c}} \right)}B^{C_{dt}}}{\left( {1 - {\alpha_{c}B}} \right)\left( {1 - B} \right)}.}$where:

B is the backward shift operator such that Bγ_(t)=γ_(t-1),B²γ_(t)=γ_(t-2), B^(k)γ_(t)=γ_(t)=γ_(t-k)

$k_{c} = \frac{ISF}{CR}$is the carb gain (in units of mg/dl/g)

${\alpha_{c} = e^{- \frac{ts}{\tau_{c}}}},$where τ_(c) is the carb time constant (for example, approximately 30min), and where ts is the sampling time (for example, a CGM may use asampling time interval of every 5 min)

c_(dt)=floor(τ_(dc)/ts), where τ_(dc) is the carb deadtime (for example,approximately 15 min) From the equation above, the second element mayrepresent the effect on blood glucose due to insulin:

$G_{i} = {\frac{{K_{i}\left( {1 - \alpha_{c}} \right)}B^{i_{dt}}}{\left( {1 - {\alpha_{i}B}} \right)\left( {1 - B} \right)}.}$where:

k_(i)=−ISF is the insulin gain (in units of mg/dl/unit)

${\alpha_{i} = e^{- \frac{ts}{\tau_{i}}}},$where τ_(i) is the insulin time constant (for example, approximately 120min)

i_(dt)=floor(τ_(ch)/ts), where τ_(di) is the insulin deadtime (forexample, approximately 30 min) From the equation above, the thirdelement may represent the effect on blood glucose due to disturbances(e.g., the AR2 disturbance model):G _(d) e ^(a) ^(t)and may be based on the following log-transformed AR2 model:

${\ln\left( \frac{{BGD}_{t}}{\mu^{*}} \right)} = {{\alpha_{1}{\ln\left( \frac{{BGD}_{t}}{\mu^{*}} \right)}} + {\alpha_{2}{\ln\left( \frac{{BGD}_{t - 2}}{\mu^{*}} \right)}} + \alpha_{t}}$which when rearranged, yields:BGd _(t) =BGd _(t-1) ^(α) ¹ BGd _(t-2) ^(α) ² μ*^((1-α) ¹ ^(-α) ² ⁾ e^(α) ^(t)where, in some examples,a _(t)˜Normal(0,σ_(a))

and

$\sigma_{\alpha} \approx {50\%\ln\mspace{14mu}\left( \sigma^{*} \right)\sqrt{\left. {{\frac{1 + \alpha_{2}}{1 - \alpha_{2}}\left( \left( {1 - \alpha_{2}} \right)^{2} \right)} - \alpha_{1}^{2}} \right)}}$with

μ*·10^(Normal (2.09, 0.08)) and σ*·10^(Normal (0.15, 0.028)) such that

α1≈1.6442, α₂≈0.6493.

Using the above notation, expansion of the initial equation for BG_(t)may be represented by the equation:

${BG}_{t} = {{\frac{k_{c}\left( {1 - \alpha_{c}} \right)}{\left( {1 - {\alpha_{c}B}} \right)\left( {1 - B} \right)}c_{t\text{-}{dt}_{c}}} + {\frac{k_{i}\left( {1 - \alpha_{i}} \right)}{\left( {1 - {\alpha_{i}B}} \right)\left( {1 - B} \right)}i_{t\text{-}{dt}_{i}}} + {{BGd}_{t\text{-}1}^{\alpha_{1}}{BGd}_{t\text{-}2}^{\alpha_{2}}\mu^{*{({1\text{-}\alpha_{1}\text{-}\alpha_{2}})}}}}$

Systems and methods provided herein can in some cases calculate anamount of insulin on board (IOB) and/or an amount of carbohydrates onboard (COB) in order to predict future blood glucose values. IOB and COBrepresent the amount of insulin and carbohydrates, respectively, whichhave been infused and/or consumed but not yet metabolized. Knowledge ofIOB and COB can be useful for a user of a method or system providedherein when it comes to bolus decisions to prevent insulin stacking, butknowledge of IOB and COB can also be used in methods and systemsprovided herein to predict future blood glucose values.

IOB and COB represent the amount of insulin and carbohydrates,respectively, which have been infused and/or consumed but not yetmetabolized. Knowledge of IOB can be useful in correcting bolusdecisions to prevent insulin stacking. Knowledge of IOB and COB can beuseful for predicting and controlling blood glucose. Both insulininfusion and carbohydrate consumption can involve deadtime ortransportation delay (e.g., it can take ten to forty minutes for insulinand/or carbohydrates to begin to affect blood glucose). During theperiod immediately after entering the body (e.g., during the deadtimeperiod), it can be beneficial to account for IOB and COB in anydecisions such as bolusing. This can be called “Decision” IOB/COB.“Action” IOB/COB, on the other hand, can represent the insulin and/orcarbohydrates available for action on blood glucose. In some cases,Decision IOB can be a displayed IOB, while Action IOB can be an IOBdetermined for use in selecting a basal delivery rate or profile inmethods and systems provided herein.

From the equations above,

${BG}_{it} = {\frac{{- {{ISF}\left( {1 - \alpha_{i}} \right)}}B^{i_{dt}}}{\left( {1 - {\alpha_{i}B}} \right)\left( {1 - B} \right)}i_{t\text{-}i_{dt}}}$where

BY_(t)=Y_(t-1), B²Y_(t)=Y_(t-2), B^(k)Y_(t)=Y_(t-k)

$\alpha_{i} = e^{- \frac{ts}{\tau_{i}}}$where τ_(i) is the insulin time constant (for example, approximately 120min) i_(dt)=floor(τ_(di)/ts), where τ_(di) is the insulin deadtime (forexample, approximately 30 min) and where τ_(s) is the sampling time (forexample, a CGM may use a sampling time interval of every 5 min)“Decision” IOB

In some embodiments, Decision IOB at time (t) (IOB Dt) may be calculatedaccording to the following mathematical process:

${IOB\_ D}_{t} = {{IOB\_ D}_{t\text{-}1} - \frac{{BGi}_{t} - {BGi}_{t\text{-}1}}{- {ISF}} + i_{t}}$or, alternatively,

${\nabla{IOB\_ D}_{t}} = {{{- \frac{1 - \alpha_{i}}{1 - {\alpha_{i}B}}}i_{t\text{-}i_{dt}}} + i_{t}}$substituting the equation above for Bat into the equation for IOB_D_(t)or ∇IOB_D_(t) yields

${IOB\_ D}_{D_{t}} = {\frac{1 - {\alpha_{i}B} - {\left( {1 - \alpha_{i}} \right)B^{i\;}{dt}}}{1 - {\left( {\alpha_{i} + 1} \right)B} + {\alpha_{i}B^{2}}}i_{t}}$or, alternatively,

${\nabla{IOB\_ D}_{t}} = {{- \frac{\nabla{BGi}_{t}}{- {ISF}}} + i_{t}}$“Action” IOB

In some embodiments, Action IOB at time (t) (IOB_A_(t)) may becalculated according to the following mathematical process:

${IOB\_ A}_{t} = {\frac{1}{1 - {\alpha_{i}B}}i_{t\text{-}i_{dt}}}$

For an arbitrary series of insulin infusions, using an infinite seriesof expansions of

$\frac{1}{1 - {\alpha_{i}B}},$IOB_A_(t) may be represented by

${IOB}_{A_{t}} = {\sum\limits_{k = 0}^{n}{\alpha_{i}^{k}i_{t\text{-}k\text{-}i_{dt}}}}$

Stated another way,

${BGi}_{t} = {\frac{- {{ISF}\left( {1 - \alpha_{i}} \right)}}{1 - B}{IOB\_ A}_{t}}$

The formulas for COB, including Action COB and Decision COB, may bedeveloped in a similar fashion, using the equation above related toG_(c):

$G_{ct} = \frac{{k_{c}\left( {1 - \alpha_{c}} \right)}B^{c}{dt}}{\left( {1 - {\alpha_{c}B}} \right)\left( {1 - B} \right)}$

Accordingly, future blood glucose data can be estimated using current orrecent blood glucose data, data about when carbohydrates were consumed,and/or data regarding when insulin was and/or will be administered.Moreover, because evaluated insulin delivery profiles and/or ratesinclude basal insulin delivery rates above and below the BBR, thoseinsulin delivery rates above BBR can be added to the IOB calculation andinsulin delivery rates below the BBR can be subtracted from the IOB. Insome cases, a variation in a Decision IOB due to actual variations fromBBR can be limited to positive deviations in order to prevent a userfrom entering an excessive bolus.

Estimating Glucose Levels from Blood Glucose Data

Referring back to FIG. 1, continuous glucose monitor 50 and bloodglucose meter 70 can both provide blood glucose data to system 10. Theblood glucose data, however, can be inaccurate. In some cases,continuous glucose monitor 50 can be replaced (or have sensor shaft 56replaced) at regular or irregular intervals (e.g., every three days,every five days, every seven days, or every ten days). In some cases,data from blood glucose meter 70 can be used to calibrate the continuousglucose monitor 50 at regular or irregular intervals (e.g., every threehours, every six hours, every twelve hours, every day, etc.). In somecases, systems and methods provided herein can remind a user to changethe continuous glucose monitor 50 or calibrate continuous glucosemonitor 50 using blood glucose meter 70 based on data from continuousglucose monitor 50 and/or at regular intervals. For example, if thepattern of insulin delivery varies greatly from an earlier predictedpattern of insulin deliveries may indicate that the continuous glucosemonitor 50 requires maintenance and/or replacement.

In some cases, methods and systems can determine an accuracy factor forblood glucose data from the continuous glucose monitor 50 based uponwhen the particular continuous glucose monitor sensor shaft 56 was firstapplied to the PWD and/or when the particular continuous glucose monitor50 was last calibrated using blood glucose data from blood glucose meter70. In some cases, methods and systems provided herein make adjustmentsto future blood glucose targets based on a calculated accuracy factorfor data from the continuous glucose monitor 50 in order to reduce arisk of hypoglycemia. In some cases, methods and systems provided hereincan estimate the current blood glucose level as being a predeterminednumber of standard deviations (e.g., 0.5 standard deviations, onestandard deviation, two standard deviations) below data received fromcontinuous glucose monitor 50 based on the accuracy factor in order toreduce a risk of hypoglycemia.

After continuous glucose monitor 50 is calibrated or replaced with a newcontinuous glucose monitor or has a new sensor shaft 56 installed,however, a discontinuity of reported glucose data from the continuousglucose monitor 50 can occur. In some cases, methods and systemsprovided herein, however, can use and report historical blood glucosevalues in selecting insulin basal rates and/or profiles. In some cases,methods and systems provided herein can revise stored and/or reportedblood glucose levels based on data from one or more continuous glucosemonitors in order to transition between different continuous glucosemonitor sensors and/or to data produced after a calibration. In somecases, a continuous glucose monitor 50 can provide each blood glucosevalue with an estimated rate of change, and the rate of changeinformation can be used to retrospectively adjust one or more historicalestimated blood glucose values from data from a continuous glucosemonitor 50. For example, the rate of change of the pre-calibrationreported blood glucose value may be used to determine an estimatedpost-calibration value assuming the same rate of change. A ratio of thepost-calibration reported blood glucose value to the estimatedpost-calibration value can then be used to linearly interpolate multiplehistorical blood glucose values based on that ratio. In some cases, allreadings between calibrations can be linearly interpolated. In somecases, data from a predetermined amount of time prior to a calibrationcan be linearly interpolated (e.g., fifteen minutes, thirty minutes, onehour, two hours, three hours, or six hours).

Analyzing Variations from Targets

Methods and systems provided herein can evaluate each future basaldelivery profile by predicting blood glucose for the basal deliveryprofiles (e.g., as illustrated in the graph 320 of FIG. 3) andcalculating a variation index of the predicted blood glucose values fromthe target blood glucose values. Methods and systems provided herein canthen select the profile of basal rate delivery actions that correspondsto the lowest variation index (e.g., the lowest value 340 of the graph330 of FIG. 3). The variation index can use a variety of differentmathematical formulas to weight different types of variations. Thevariation index can be a cost function. In some cases, methods andsystems provided herein can use a cost function that sums up squares ofdifferences for the projected blood glucose values from target bloodglucose values for multiple diurnal time segments. Methods and systemsprovided herein can use any suitable cost function. In some cases, costfunctions can sum the absolute value of the difference between eachpredicted blood glucose value and each blood glucose target. In somecases, cost functions used in methods and systems provided herein canuse a square of the difference. In some cases, cost functions used inmethods and systems provided herein can use a square of the differencebetween the logs of each predicted blood glucose level and eachcorresponding blood glucose target. In some cases, cost functions usedin methods and systems provided herein can assign a higher cost to bloodglucose values below the blood glucose target in order reduce the riskof a hypoglycemic event. FIG. 3 depicts the “loss” (i.e., the resultingvalue for a cost function) for the plurality of basal delivery profiles.As shown in FIG. 3, the basal delivery profile 11, 310 k, corresponds tothe lowest value 340. In some cases, a profile that has the lowest valueof loss may be selected. In some cases, cost functions provided hereincan include elements that additional bias the selected profile toward aprofile that maintains the previously administered basal rate and/orthat delivers the baseline basal rate, which may prevent the system fromchanging delivery rates every time a basal delivery profile or rate isselected in Block 265. In some cases, the cost function can square thedifference between the log of the values in order to provide a highercost for projected lows than projected highs.

Selecting a Basal Insulin Delivery Profile or Rate

Methods and systems provided herein can then select a basal profile orrate that produces the lowest cost function value. As shown in FIG. 3,the delivery profile 11, 310 k, has the lowest loss, and is thus theselected profile for delivery. With reference to FIG. 2, at block 272insulin can then be delivered according to the selected profile for anamount of time. In some cases, the amount of time is a predeterminedamount of time. In some cases, the predetermined amount of time is lessthan the time horizon for the estimated future blood glucose values andthe length of time for the selected basal delivery profile. In somecases, the predetermined amount of time is ninety minutes or less, sixtyminutes or less, forty-five minutes or less, thirty minutes or less,twenty minutes or less, fifteen minutes or less, ten minutes or less, orfive minutes or less. After the period of time, the system can againrepeat the operations at blocks 263, 264, 265, and 272 to select anddeliver a basal insulin for a subsequent period of time.

Adjusting User-Specific Dosage Parameters

Methods and systems provided herein can make adjustments to theuser-specific dosage parameters. For example, FIG. 2 includes the block281 for detecting time periods when an amount of delivered basal insulinis different from a BBR, which can then be used to adjust user-specificdosage parameters at block 262. These updated user-specific dosageparameters can then be used to generate new basal delivery profiles atblock 263 and used at block 264 to evaluate different basal deliveryprofiles. For example, for a BBR of 1.46 U/hour (associated with a TDBof 35 U/day), if a diurnal period under consideration is one hour andfor the first forty-five minutes, insulin was delivered at a rate of2.92 U/hour (e.g., 2× the BBR) and only the last fifteen minutes wasdelivered at a rate of 1.46 U/hour (e.g., 1× the BBR), user-specificdosage parameters for a related diurnal time period (e.g., that samehour on another day in the future, or a preceding diurnal time period ona day in the future) may be adjusted.

In some cases, methods and systems provided herein can make adjustmentsfor BBR, ISF, and/or CR for multiple diurnal periods based on variationsin the insulin amounts actually delivered for that diurnal periodcompared to the baseline basal insulin rate for that diurnal period. Insome cases, diurnal periods can have a same length of time as apredetermined length of time for the delivery of a selected insulindelivery. In some cases, a diurnal period can be greater than apredetermined length of time for the delivery of a selected insulindelivery, for example, multiple doses of insulin may be delivered duringa single diurnal period. In some cases, a diurnal period can be fifteenminutes, thirty minutes, one hour, two hours, etc. In some cases, anactual delivery of insulin for a diurnal period must surpass apredetermined threshold above or below the BBR for that diurnal periodin order for user-specific dosage parameters (e.g., BBR, ISF, CR) to beadjusted for that diurnal period. For example, diurnal periods can beone hour long, but each basal delivery profile can be delivered forfifteen minute time periods before methods and systems provided hereindetermine a new basal insulin delivery profile, and methods and systemsprovided herein can require that the total basal insulin delivery forthe diurnal period be at least greater than 50% of the BBR to increasethe BBR for that diurnal period or at 50% or less than the BBR todecrease the BBR for that diurnal period. Using the example from above,for a BBR of 1.46 U/hour, if a diurnal period under consideration is onehour and for the first forty-five minutes (e.g., three iterations ofprofile generation and delivery actions), insulin was delivered at arate of 2.92 U/hour (e.g., 2× the BBR) and only the last fifteen minutes(e.g., one iteration of profile generation and delivery action) wasdelivered at a rate of 1.46 U/hour (e.g., 1× the BBR), the total amountdelivered would be at 175% of the BBR for the one hour diurnal period,or an average ratio of 1.75x the BBR. In some cases, because the 175%exceeded 150% of the BBR, methods and systems of the present disclosuremay adjust user-specific dosage parameters. As another example using thesame 1.46 U/hour BBR and a two hour diurnal time period and deliveryprofiles reformulated every fifteen minutes, if the first forty-fiveminutes delivered no insulin (0× the BBR) and the last hour and fifteenminutes delivered 1.46 U/hour, the total amount delivered may be 62.5%of the BBR, or 0.625× of the BBR. In some cases, because the 62.5% didnot drop below 50% of the BBR, methods and systems of the presentdisclosure may not adjust the user-specific dosage parameters and maymaintain the user-specific dosage parameters for the particular diurnalperiod.

An adjustment to the CR, ISF, and BBR can be any suitable amount. Insome cases, the adjustment to the BBR is less than the differencebetween the delivered basal insulin and the previously programmed BBR.In some cases, a change to each user-specific dosage parameter (e.g.,BBR, ISF, and CR) is at a predetermined percentage or value. Forexample, in some cases, each of BBR and ISF can be increased by 5%, 3%,or 1% and CR decreased by the same percent for every period where theamount of delivered basal insulin exceeds the BBR by at least 25%. Insome cases, BBR and ISF can be decreased by 5%, 3%, or 1% and CRincreased by the same percent for every period where the amount ofdelivered basal insulin exceeds the BBR by at least 25%. By setting eachadjustment at a low level, methods and systems provided herein caneventually be personalized for the PWD without over adjusting the systembased on an unusual day (e.g., to mitigate the risk of short termdisturbances being mistaken for changes in physiological parameters). Insome cases, the adjustment to CR, ISF, and BBR may be based on arelationship between CR, ISF, and BBR, rather than a fixed amount orpercentage. In some cases, CR, ISF, and BBR can be adjusted based on apredetermined relationship between their log-transformed values. In somecases, the adjustments to CR, ISF, and BBR may be performedindependently. In these and other cases, systems and methods providedherein can monitor for variations in adjustments to CR, ISF, and/or BBRaway from a relationship between CR, ISF, and BBR. In such cases, anotification may be provided to a user (e.g., the PWD or a health careprovider) that the systems and methods of the present disclosure hadadjusted one or more user-specific dosage guidelines outside of or awayfrom a relationship between CR, ISF, and BBR.

In some cases, systems and methods provided herein can update or adjustuser-specific operating parameters for select time blocks everytwenty-four hours. In some cases, diurnal periods can be updateddynamically (e.g., immediately after a basal delivery profile or rate isselected). In some cases, diurnal periods can be updated by reusablepump controller 200, by mobile computing device 60, or using a remoteserver in the cloud. In some cases, the length of diurnal periods canvary depending on the time of day (e.g., nighttime diurnal periods couldbe longer) or depending on the user-specific dosage parameter (e.g.,BBRs might have fifteen minute diurnal periods while the CR and ISFmight have one hour diurnal periods).

In some cases, when performing an adjustment, a related diurnal periodmay be adjusted based on variation from the BBR for a given diurnalperiod. For example, if an adjustment were to be performed becausedelivery from 2 PM to 3 PM exceeded 150% of the BBR, an adjustment maybe made to the user-specific dosage parameters for the same time on adifferent day in the future (e.g., 2 PM to 3 PM on the next day) or apreceding diurnal period on a different day in the future (e.g., 1 PM to2 PM on the next day or 12 PM to 1 PM on the next day, etc.). In somecases, modifying a preceding diurnal period may adjust moreappropriately for variations in BBR and/or other user-specific dosageparameters because of the delay of effect after delivery of insulinand/or the delay of effect after consumption of carbohydrates (e.g., ifa PWD repeatedly goes high between 2 PM and 3 PM, the PWD may needadditional insulin during the 1 PM to 2 PM hour).

In some cases, systems and methods disclosed herein can smoothadjustments to user-specific dosage parameters in one diurnal periodrelative to other diurnal periods. For example, in some cases, aproposed adjustment to a BBR for a first diurnal period may be comparedto one or more preceding diurnal periods and one or more followingdiurnal periods. If the proposed adjustment is a threshold amountdifferent from one or more of the preceding or following diurnal periodvalues, the proposed adjustment may be modified to avoid drastic jumpsbetween diurnal periods. For example, if a preceding diurnal period hada BBR of 1.06 U/hour and the proposed adjustment was from a BBR of 1.4U/hour to a BBR of 1.90 U/hour, the adjustment may be reduced to smooththe transition from the preceding diurnal time period. In some cases,the smoothing may include adjusting preceding or following diurnal timeperiods in addition to the diurnal time period under consideration. Inthese and other cases, such adjustment may be performed once per day orat another periodic time such that following diurnal periods may havealready occurred and the smoothing is not being performed based onprojections. For example, the diurnal period from 1 PM to 2 PM may beanalyzed for potential adjustment at 4 PM such that the diurnal periodsfrom 11 AM to 12 PM and 12 PM to 1 PM and from 2 PM to 3 PM and 3 PM and4 PM are available in considering any adjustment and/or smoothing toperform on the user-specific dosage parameters for the 1 PM to 2 PMdiurnal period.

In some cases, systems and methods disclosed herein can adjustuser-specific dosage parameters in a diurnal period based on the FHI.For example, if the FHI is high (e.g., indicating a preference that thePWD not go low), the range for adjusting the BBR may be limited to arelatively small change (e.g., 0.5%, 1%, 1.5%, etc.). As anotherexample, if the FHI is low (e.g., indicating that the PWD is not asconcerned about going low), the range for adjusting the BBR may includea broader range of changes (e.g., up to a 5% change).

Adjusting Blood Glucose Targets

Methods and systems provided herein can make adjustments to the bloodglucose targets. For example, FIG. 2 includes the block 283 foranalyzing the variability of CGM and/or BGM data (e.g., data from theCGM 50 and/or the BGM 70 of FIG. 1), which can then be used to adjustblood glucose targets at the block 261. In some cases, blood glucosetargets are set for diurnal periods. In some cases, the diurnal periodsfor blood glucose targets are at least fifteen minutes long, at leastthirty minutes long, at least one hour long, or at least two hours long.In some cases, blood glucose targets can have a constrained range. Insome cases, blood glucose targets must be at least 80 mg/dL, at least 90mg/dL, at least 100 mg/dL, at least 110 mg/dL, or at least 120 mg/dL. Insome cases, blood glucose targets must be no greater than 200 mg/dL, nogreater than 180 mg/dL, no greater than 160 mg/dL, no greater than 140mg/dL, or no greater than 125 mg/dL. In some cases, a constrained rangeis between 100 mg/dL and 160 mg/dL. These updated blood glucose targetscan then be used at block 264 to evaluate different basal deliveryprofiles.

Updated blood glucose targets for a particular diurnal period can bebased on historical blood glucose patterns for the PWD and the risk ofhypoglycemia for the PWD over the course of a day. The updated bloodglucose targets can also consider a set FHI. For example, based on anFHI selection, an initial blood glucose target at a conservative level(e.g. 120 mg/dl) can be set, and over the course of a period of daysand/or weeks as more information is gained about variability patterns,the blood glucose target(s) can be adjusted. A slow adjustment canprevent the blocks 283 and 261 from overreacting to short termdisturbances but still allow blood glucose target individualization to aPWD's lifestyle and habits over time.

In some cases, methods and systems provided herein can also allow a userto temporarily or permanently adjust blood glucose targets by adjustingtheir fear of hypoglycemia index (FHI). In some cases, a user adjustmentto FHI can result in blood glucose targets being temporarily orpermanently adjusted to blood glucose targets based on the variabilityof CGM (and optionally BGM) data for multiple diurnal periods. In somecases, a user adjustment to FHI can add or subtract a predeterminedvalue from a previously used blood glucose target (e.g., an adjustmentfrom “prefer low” to “prefer medium” could add 20 mg/dL to each storedblood glucose target). In some cases, a temporary adjustment to FHIcould analyze variability data for multiple time blocks and set a newblood glucose target for each diurnal period based on the variabilitydata for that time block (e.g., an adjustment from “prefer low” to“prefer medium” could adjust the blood glucose target for each diurnalperiod from a level estimated to send the PWD below a threshold of 70mg/dL about 5% of the time to a level estimated to send the PWD below athreshold of 70 mg/dL about 3% of the time).

Allowing a PWD to change the FHI for temporary time periods or otherwiseuse some form of temporary override may allow a PWD to tell the systemthat the PWD is about to or is experiencing some activity or conditionthat might impact their blood glucose levels. For example, a PWD that isabout to exercise might set a temporary FHI of “prefer high” to offsetthe risk that exercise will send the PWD low for that period of time. Insome cases, a PWD might set a temporary FHI of “prefer low” if the PWDis feeling sick in order to offset the risk that the sickness willresult in high blood glucose levels. In some embodiments, such atemporary override may be a separate setting or entry other than theFHI. In these and other cases, in addition to a preferred range (e.g.,“high” or “low”), the user may be able to select a temporary override ofa target blood glucose level or range (e.g., approximately 120 mg/dL orbetween 120 mg/dL and 200 mg/dL, etc.), or may select a particularactivity or circumstance the PWD will participate in or is experiencing(e.g., exercising, sickness, menses, driving, etc.).

In some cases, after a temporary override is input, methods and systemsof the present disclosure can select a new profile to follow based onthe profile more closely aligning with the temporary override. In theseand other cases, a new set of profiles can be generated before selectingthe new profile. Additionally or alternatively, after a temporaryoverride is input, methods and systems of the present disclosure cantemporarily modify the BBR. In some cases, after the BBR has beenmodified, a new set of profiles may be generated based on thetemporarily modified BBR.

In some cases, a log of temporary overrides can be generated. Forexample, each time a user (e.g., the PWD) inputs an override, an entrycan be created in the log that includes what override was selected, whatstarting and ending times, and/or what the reason for the override was.In these and other cases, the log can be periodically provided to ahealthcare professional, for example, via email or some other electronicmessage. Additionally or alternatively, in some cases, the log can beparsed for patterns. For example, the PWD may input a temporary overrideevery Monday, Wednesday, and Friday from 6 PM to 7 PM when the PWDexercises. The log can be parsed to find such patterns of overrides. Inthese and other cases, methods and systems of the present disclosure canmodify a BBR based on the patterns. Continuing the example, the BBR maybe lowered for the diurnal period of 6 PM to 7 PM on Monday, Wednesday,and Friday because of a PWD repeatedly entering a temporary overrideduring that diurnal period that the PWD is exercising and not to go low.

Overall System

Methods and systems provided herein can control basal insulin deliveryover time and adjust basal user-specific dosage parameters and bloodglucose targets for multiple diurnal periods to personalize theuser-specific dosage parameters over time. For example, FIG. 5illustrates various examples of user interfaces (e.g., 400, 410, 420,and 430) displaying various aspects of the present disclosure.

In some cases, FIG. 5 illustrates a simulation of a method providedherein, showing how methods and systems provided herein may generate auser interface 400 that may illustrate BBRs 401, CRs 402, ISFs 403, andblood glucose targets 404 set for multiple time blocks. For example,after a system (e.g., the system 10 of FIG. 1) has run on a PWD afterthirty days, user-specific dosage parameters may be personalized basedon adjustments made to the user-specific dosage parameters. For example,the user interface 400 may align the various user-specific dosageparameters over various diurnal periods throughout a day. For example,the BBR 401 may be higher around meal times (e.g., nine AM, twelve PM,and seven PM), and lower while the PWD is sleeping (e.g., eleven PM tofive AM). As an additional example, the CR 402 and ISF 403 may follow asimilar trajectory of variation as illustrated for the BBR 401.

In some cases, as illustrated in user interface 410 of FIG. 5, methodsand/or systems of the present disclosure (including, for example,back-end computer systems) may monitor and/or track blood glucose levelsover time. For example, the user interface 410 may illustrate glucoselevels for one hundred and eighty days, with a bar indicating the lastthirty days. In some cases, when adjusting user-specific dosageparameters, methods and systems of the present disclosure may disregardreadings older than thirty days, or may weight more recent readings moreheavily than older readings.

In some cases, the user interface 420 may include time aligned charts(including chart 421, chart 422, and chart 423) that can show a six hourwindow of the timeline illustrated in user interface 410. As illustratedin FIG. 5, chart 421 depicts the current blood glucose values as well asthe predictions that have been made over time for that particulardelivery time. For example, once the “current” bar 424 is reached, theremay have been multiple predictions made for each time segment. As thewindow extends further into the future, the number of predictions may belower. The chart 422 illustrates the calculated IOB and the calculatedCOB for the PWD. The chart 423 indicates whether the method or systemdelivered 0% of the BBR, 100% of the BBR, or 200% of the BBR for fifteenminute time segments.

As illustrated in FIG. 5, the user interface 430 depicts a possible userinterface for a PWD showing some data that may be displayed on a mobiledevice of a PWD (e.g., the mobile computing device 60 of FIG. 1). Insome cases, only the data prior to the bar 424 (e.g., historic data) maybe shown in the user interface 430. In a first part 431 of the userinterface 430, historic blood glucose data can be displayed. In a secondsection 432, announced meals and bolus insulin deliveries can bedisplayed. In a third section 433, the rates of basal delivery can bedisplayed. The third section 433 can differ from chart 423 by displayingthe actual rates of basal delivery rather than a ratio of the ratedelivered to the BBR. Section 434 can display a current blood glucosereading, a current IOB, and/or an indication of whether the system isautomating. In some cases, more or less information can be displayed onthe user interface 430 than illustrated in FIG. 5. For example, the userinterface 430 may include any of the information from the userinterfaces 400, 410, and/or 420 in any combination.

Additional Details about Example Pump Assembly

FIGS. 6A and 6B provide additional details about example pump assembly15 as discussed above in regards to FIG. 1. FIG. 6B depicts the detailsof example reusable pump controller 200.

Referring now to FIG. 6A, disposable pump 100 in this embodimentincludes a pump housing structure 110 that defines a cavity 116 in whicha fluid cartridge 120 can be received. Disposable pump 100 also caninclude a cap device 130 to retain the fluid cartridge 120 in the cavity116 of the pump housing structure 110. Disposable pump 100 can include adrive system (e.g., including a battery powered actuator, a gear system,a drive rod, and other items that are not shown in FIG. 6A) thatadvances a plunger 125 in the fluid cartridge 120 so as to dispensefluid therefrom. In this embodiment, reusable pump controller 200communicates with disposable pump 100 to control the operation of thedrive system. For example, in some cases, the reusable pump controller200 can generate a message for the disposable pump 100 directing thedisposable pump 100 to deliver a certain amount of insulin or deliverinsulin at a certain rate. In some cases, such a message may direct thedisposable pump 100 to advance the plunger 125 a certain distance. Insome cases, not depicted, reusable pump controller 200 may include auser interface to control the operation of disposable pump 100. In somecases, disposable pump 100 can be disposed of after a single use. Forexample, disposable pump 100 can be a “one-time-use” component that isthrown away after the fluid cartridge 120 therein is exhausted.Thereafter, the user can removably attach a new disposable pump 100(having a new fluid cartridge) to the reusable pump controller 200 forthe dispensation of fluid from a new fluid cartridge. Accordingly, theuser is permitted to reuse reusable pump controller 200 (which mayinclude complex or valuable electronics, as well as a rechargeablebattery) while disposing of the relatively low-cost disposable pump 100after each use. Such a pump assembly 15 can provide enhanced user safetyas a new pump device (and drive system therein) is employed with eachnew fluid cartridge.

The pump assembly 15 can be a medical infusion pump assembly that isconfigured to controllably dispense a medicine from the fluid cartridge120. As such, the fluid cartridge 120 can contain a medicine 126 to beinfused into the tissue or vasculature of a targeted individual, such asa human or animal patient. For example, disposable pump 100 can beadapted to receive a fluid cartridge 120 in the form of a carpule thatis preloaded with insulin or another medicine for use in the treatmentof diabetes (e.g., Exenatide (BYETTA®, BYDUREON®) and liraglutide(VICTOZA®) SYMLIN®, or others). Such a fluid cartridge 120 may besupplied, for example, by Eli Lilly and Co. of Indianapolis, Ind. Thefluid cartridge 120 may have other configurations. For example, thefluid cartridge 120 may comprise a reservoir that is integral with thepump housing structure 110 (e.g., the fluid cartridge 120 can be definedby one or more walls of the pump housing structure 110 that surround aplunger to define a reservoir in which the medicine is injected orotherwise received).

In some embodiments, disposable pump 100 can include one or morestructures that interfere with the removal of the fluid cartridge 120after the fluid cartridge 120 is inserted into the cavity 116. Forexample, the pump housing structure 110 can include one or more retainerwings (not shown) that at least partially extend into the cavity 116 toengage a portion of the fluid cartridge 120 when the fluid cartridge 120is installed therein. Such a configuration may facilitate the“one-time-use” feature of disposable pump 100. In some embodiments, theretainer wings can interfere with attempts to remove the fluid cartridge120 from disposable pump 100, thus ensuring that disposable pump 100will be discarded along with the fluid cartridge 120 after the fluidcartridge 120 is emptied, expired, or otherwise exhausted. In anotherexample, the cap device 130 can be configured to irreversibly attach tothe pump housing structure 110 so as to cover the opening of the cavity116. For example, a head structure of the cap device 130 can beconfigured to turn so as to threadably engage the cap device 130 with amating structure along an inner wall of the cavity 116, but the headstructure may prevent the cap device from turning in the reversedirection so as to disengage the threads. Accordingly, disposable pump100 can operate in a tamper-resistant and safe manner because disposablepump 100 can be designed with a predetermined life expectancy (e.g., the“one-time-use” feature in which the pump device is discarded after thefluid cartridge 120 is emptied, expired, or otherwise exhausted).

Still referring to FIG. 6A, reusable pump controller 200 can beremovably attached to disposable pump 100 so that the two components aremechanically mounted to one another in a fixed relationship. In someembodiments, such a mechanical mounting can also form an electricalconnection between the reusable pump controller 200 and disposable pump100 (for example, at electrical connector 118 of disposable pump 100).For example, reusable pump controller 200 can be in electricalcommunication with a portion of the drive system (not shown) ofdisposable pump 100. In some embodiments, disposable pump 100 caninclude a drive system that causes controlled dispensation of themedicine or other fluid from the fluid cartridge 120. In someembodiments, the drive system incrementally advances a piston rod (notshown) longitudinally into the fluid cartridge 120 so that the fluid isforced out of an output end 122. A septum 121 at the output end 122 ofthe fluid cartridge 120 can be pierced to permit fluid outflow when thecap device 130 is connected to the pump housing structure 110. Forexample, the cap device 130 may include a penetration needle thatpunctures the septum 121 during attachment of the cap device 130 to thepump housing structure 110. Thus, when disposable pump 100 and reusablepump controller 200 are mechanically attached and thereby electricallyconnected, reusable pump controller 200 communicates electronic controlsignals via a hardwire-connection (e.g., electrical contacts alongelectrical connector 118 or the like) to the drive system or othercomponents of disposable pump 100. In response to the electrical controlsignals from reusable pump controller 200, the drive system ofdisposable pump 100 causes medicine to incrementally dispense from thefluid cartridge 120. Power signals, such as signals from a battery (notshown) of reusable pump controller 200 and from the power source (notshown) of disposable pump 100, may also be passed between reusable pumpcontroller 200 and disposable pump 100.

Referring again to FIGS. 1 and 5A, the pump assembly 15 can beconfigured to be portable and can be wearable and concealable. Forexample, a PWD can conveniently wear the pump assembly 15 on the PWD'sskin (e.g., skin adhesive) underneath the PWD's clothing or carrydisposable pump 100 in the PWD's pocket (or other portable location)while receiving the medicine dispensed from disposable pump 100. Thepump assembly 15 depicted in FIG. 1 as being held in a PWD's hand 5 soas to illustrate the size of the pump assembly 15 in accordance withsome embodiments. This embodiment of the pump assembly 15 is compact sothat the PWD can wear the pump assembly 15 (e.g., in the PWD's pocket,connected to a belt clip, adhered to the PWD's skin, or the like)without the need for carrying and operating a separate module. In suchembodiments, the cap device 130 of disposable pump 100 can be configuredto mate with an infusion set 146. In general, the infusion set 146 canbe a tubing system that connects the pump assembly 15 to the tissue orvasculature of the PWD (e.g., to deliver medicine into the tissue orvasculature under the PWD's skin). The infusion set 146 can include atube 147 that is flexible and that extends from disposable pump 100 to asubcutaneous cannula 149 that may be retained by a skin adhesive patch(not shown) that secures the subcutaneous cannula 149 to the infusionsite. The skin adhesive patch can retain the cannula 149 in fluidcommunication with the tissue or vasculature of the PWD so that themedicine dispensed through the tube 147 passes through the cannula 149and into the PWD's body. The cap device 130 can provide fluidcommunication between the output end 122 (FIG. 6A) of the fluidcartridge 120 and the tube 147 of the infusion set 146. As shown inFIGS. 6A and 6B, controller housing 210 may define an opening 230adapted to enable the tube 147 to pass through.

In some embodiments, the pump assembly 15 can be pocket-sized so thatdisposable pump 100 and reusable pump controller 200 can be worn in thePWD's pocket or in another portion of the PWD's clothing. In somecircumstances, the PWD may desire to wear the pump assembly 15 in a morediscrete manner. Accordingly, the PWD can pass the tube 147 from thepocket, under the PWD's clothing, and to the infusion site where theadhesive patch can be positioned. As such, the pump assembly 15 can beused to deliver medicine to the tissues or vasculature of the PWD in aportable, concealable, and discrete manner.

In some embodiments, the pump assembly 15 can be configured to adhere tothe PWD's skin directly at the location in which the skin is penetratedfor medicine infusion. For example, a rear surface of disposable pump100 can include a skin adhesive patch so that disposable pump 100 can bephysically adhered to the skin of the PWD at a particular location. Inthese embodiments, the cap device 130 can have a configuration in whichmedicine passes directly from the cap device 130 into an infusion set146 that is penetrated into the PWD's skin. In some examples, the PWDcan temporarily detach reusable pump controller 200 (while disposablepump 100 remains adhered to the skin) so as to view and interact withthe user interface 220.

In some embodiments, the pump assembly 15 can operate during anautomated mode to deliver basal insulin according the methods providedherein. In some cases, pump assembly 15 can operate in an open loop modeto deliver insulin at the BBR. A basal rate of insulin can be deliveredin an incremental manner (e.g., dispense 0.10 U every five minutes for arate of 1.2 U per hour) according to a selected basal insulin deliveryprofile. A user can use the user interface on mobile computing device 60to select one or more bolus deliveries, for example, to offset the bloodglucose effects caused by food intake, to correct for an undesirablyhigh blood glucose level, to correct for a rapidly increasing bloodglucose level, or the like. In some circumstances, the basal ratedelivery pattern may remain at a substantially constant rate for a longperiod of time (e.g., a first basal dispensation rate for a period ofhours in the morning, and a second basal dispensation rate for a periodof hours in the afternoon and evening). In contrast, the bolus dosagescan be more frequently dispensed based on calculations made by reusablepump controller 200 or the mobile computing device 60 (which thencommunicates to reusable pump controller 200). For example, reusablepump controller 200 can determine that the PWD's blood glucose level israpidly increasing (e.g., by interpreting data received from thecontinuous glucose monitor 50), and can provide an alert to the user(via the user interface 220 or via the mobile computing device 60) sothat the user can manually initiate the administration of a selectedbolus dosage of insulin to correct for the rapid increase in bloodglucose level. In one example, the user can request (via the userinterface of mobile computing device 60) a calculation of a suggestedbolus dosage (e.g., calculated at the mobile computing device 60 basedupon information received from the user and from reusable pumpcontroller 200, or alternatively calculated at reusable pump controller200 and communicated back via the mobile computing device 60 for displayto the user) based, at least in part, on a proposed meal that the PWDplans to consume.

Referring now to FIG. 6B, reusable pump controller 200 (shown in anexploded view) houses a number of components that can be reused with aseries of successive disposable pumps 100. In particular, reusable pumpcontroller 200 can include control circuitry 240 (e.g., a controldevice) and a rechargeable battery pack 245, each arranged in thecontroller housing 210. The rechargeable battery pack 245 may provideelectrical energy to components of the control circuitry 240, othercomponents of the controller device (e.g., a display device and otheruser interface components, sensors, or the like), or to components ofdisposable pump 100. The control circuitry 240 may be configured tocommunicate control or power signals to the drive system of disposablepump 100, or to receive power or feedback signals from disposable pump100.

The control circuitry 240 of reusable pump controller 200 can includeone or more microprocessors 241 configured to execute computer-readableinstructions stored on one or more memory devices 242 so as to achieveany of the control operations described herein. At least one memorydevice 242 of the control circuitry 240 may be configured to store anumber of user-specific dosage parameters. One or more user-specificdosage parameters may be input by a user via the user interface 220.Further, as described below in connection with FIG. 6A, varioususer-specific dosage parameters can be automatically determined and/orupdated by control operations implemented by the control circuitry 240of reusable pump controller 200. For example, the control circuitry 240can implement a secondary feedback loop to determine and/or update oneor more user-specific dosage parameters in parallel with the diabetesmanagement system 10 operating in a closed-loop delivery mode. Whetherdetermined automatically or received via the mobile computing device 60(or via the user interface 220 of reusable pump controller 200), thecontrol circuitry 240 can cause the memory device 242 to store theuser-specific dosage parameters for future use during operationsaccording to multiple delivery modes, such as closed-loop and open-loopdelivery modes. Additionally, the control circuitry 240 can causereusable pump controller 200 to periodically communicate theuser-specific dosage parameters to the mobile computing device 60 forfuture use during operations by the mobile computing device 60 or forsubsequent communication to a cloud-based computer network.

Such user-specific dosage parameters may include, but are not limitedto, one or more of the following: total daily basal dosage limits (e.g.,in a maximum number of units/day), various other periodic basal dosagelimits (e.g., maximum basal dosage/hour, maximum basal dosage/six hourperiod), insulin sensitivity (e.g., in units of mg/dL/insulin unit),carbohydrate ratio (e.g., in units of g/insulin unit), insulin onsettime (e.g., in units of minutes and/or seconds), insulin on boardduration (e.g., in units of minutes and/or seconds), and basal rateprofile (e.g., an average basal rate or one or more segments of a basalrate profile expressed in units of insulin unit/hour). Also, the controlcircuitry 240 can cause the memory device 242 to store (and can causereusable pump controller 200 to periodically communicate out to themobile computing device 60) any of the following parameters derived fromthe historical pump usage information: dosage logs, average total dailydose, average total basal dose per day, average total bolus dose perday, a ratio of correction bolus amount per day to food bolus amount perday, amount of correction boluses per day, a ratio of a correction bolusamount per day to the average total daily dose, a ratio of the averagetotal basal dose to the average total bolus dose, average maximum bolusper day, and a frequency of cannula and tube primes per day. To theextent these aforementioned dosage parameters or historical parametersare not stored in the memory device 242, the control circuitry 240 canbe configured to calculate any of these aforementioned dosage parametersor historical parameters from other data stored in the memory device 242or otherwise input via communication with the mobile computing device60.

FIG. 7 illustrates a flow diagram of an example method 600 of usinginsulin delivery profiles. The method 600 may be performed by anysuitable system, apparatus, or device. For example, the system 10, thepump assembly 15, the mobile computing device 60 of FIG. 1, and/or aremote server may perform one or more of the operations associated withthe method 600. Although illustrated with discrete blocks, the steps andoperations associated with one or more of the blocks of the method 600may be divided into additional blocks, combined into fewer blocks, oreliminated, depending on the desired implementation.

At block 610, a set of insulin delivery profiles can be generated, eachhaving a series of insulin delivery actions. For example, the pumpassembly 15 may generate a series of potential delivery actions that mayinclude permutations based on one or more potential inflection points inthe delivery actions (e.g., the permutations illustrated in the chart300 of FIG. 3).

At block 620, a prediction can be made of future blood glucose levelsfor each of the delivery profiles. For example, the pump assembly 15and/or the mobile computing device 60 of FIG. 1 can generate aprediction of future blood glucose levels at various points in time if aparticular profile is followed. Such prediction may be based on theeffect of glucose, insulin, carbohydrates, and/or other disturbancesprojected for the blood glucose levels at the various points in time.

At block 630, a determination can be made as to variations from a targetblood glucose level for each of the profiles. For example, the pumpassembly 15 and/or the mobile computing device 60 of FIG. 1 may comparethe predicted blood glucose levels to a target blood glucose level foreach of the various points in time. In some cases, the target bloodglucose level may be constant and in other cases, the target bloodglucose level may vary over time. In these and other cases, thevariation may be measured as a distance between the target blood glucoselevel and the projected blood glucose level, or a square of thedifference, etc. as described above.

At block 640, the profile that approximates the target blood glucoselevel can be selected. In some cases, the profile that minimizesvariation from the target blood glucose level may be selected. Forexample, a cost function can be utilized and the profile with the lowestcost can be selected as the profile that approximates the target bloodglucose level.

At block 650, insulin may be delivered based on the next action in theselected profile. For example, control circuitry 240 of the pumpassembly 15 may send a message to the pump portion of the pump assembly15 to deliver insulin based on the next action in the selected profile.For example, a next action may indicate that the pump is to deliver Ox,lx, or 2 x of a BBR. The next action can be the first delivery action inthe set of actions of the profile.

In some cases, after the block 650, the method 600 can return to theblock 610 to generate another set of insulin delivery profiles, predictfuture blood glucose levels, determine variations from a target bloodglucose level, etc. In some cases, the method 600 can be performediteratively each time a PWD is to receive a dose of basal insulin. Inthese and other cases, the method 600 can routinely update deliveryactions based on a repeatedly updated projection of the blood glucoselevels of the PWD and the effect a particular delivery action may haveon the blood glucose levels. In some cases, methods and systems providedherein can change modes if there is a lack of reliable CGM data at thispoint in time (e.g., the system can change modes to a mode where BBR isdelivered and potentially provide notice that the system has exited theautomation mode).

Modifications, additions, or omissions may be made to the method 600without departing from the scope of the present disclosure. For example,the operations of the method 600 may be implemented in differing order.Additionally or alternatively, two or more operations may be performedat the same time. Furthermore, the outlined operations and actions areprovided as examples, and some of the operations and actions may beoptional, combined into fewer operations and actions, or expanded intoadditional operations and actions without detracting from the essence ofthe disclosed embodiments.

FIG. 8 illustrates a flow diagram of an example method 700 of adjustinginsulin delivery rates. The method 700 may be performed by any suitablesystem, apparatus, or device. For example, the system 10, the pumpassembly 15, the mobile computing device 60 of FIG. 1, and/or a remoteserver may perform one or more of the operations associated with themethod 700. Although illustrated with discrete blocks, the steps andoperations associated with one or more of the blocks of the method 700may be divided into additional blocks, combined into fewer blocks, oreliminated, depending on the desired implementation.

At block 710, insulin can be delivered over a diurnal time period. Forexample, the pump assembly 15 of FIG. 1 can deliver insulin to a PWDbased on a BBR for the diurnal time period. In some cases, the insulinmay be actually delivered at multiple points in time throughout thediurnal time period as a ratio of the BBR, such as 0×, 1×, and 2×.

At block 720, variations between actual insulin delivered values and theBBR for the diurnal time period can be determined. For example, if thedelivery actions throughout the diurnal time period deliver a ratio ofthe BBR, the actual delivery actions may be averaged over the diurnaltime period to find an average ratio for the diurnal time period. Inthese and other cases, the actual insulin delivered values can be basedon periodically projected blood glucose levels and the BBR. For example,a set of insulin delivery profiles can be generated and a deliveryaction selected as described in the present disclosure (e.g., asdescribed in FIG. 7).

At block 730, a determination is made as to whether the variationsbetween the actual insulin delivered values and the baseline basalinsulin rate exceeds a threshold. If the variations do exceed thethreshold, the method 700 may proceed to the block 740. If thevariations do not exceed the threshold, the method 700 may proceed backto the block 710. In some cases, the threshold may be based on a ratioof the baseline basal delivery rate. For example, the threshold mayinclude that the average rate over the diurnal period be above 150% ofthe BBR or below 50% of the BBR for the actual delivery values over thediurnal time period.

At block 740, the baseline basal insulin rate can be adjusted for arelated diurnal time period. For example, the BBR can be adjusted higherby a certain amount (e.g., 1%, 2%, or 5%) if the variations went above athreshold and can be adjusted lower by a certain amount (e.g., 1%, 2%,or 5%) if the variations went below a threshold. In some cases, therelated diurnal time period can be the same block of time (e.g., if thevariations exceeded the threshold during the 2 PM to 3 PM diurnalperiod, then the BBR from 2 PM to 3 PM of the next day may be adjusted)on another day in the future, and in some cases, the related diurnaltime period can be a different time on another day (e.g., if thevariations exceeded the threshold during the 2 PM to 3 PM diurnalperiod, then the BBR from 1 PM to 2 PM of the next day may be adjusted).In some cases, such an adjustment may be performed once per day for allthe diurnal periods of that day.

In some cases, the adjustment at block 740 can include smoothing of theadjustment. For example, a potential modification can be compared to theBBR of the preceding diurnal time period or the following diurnal timeperiod, and may modify the adjustment to be closer to the other diurnaltime periods. Additionally or alternatively, the BBR can be smoothed bycomparing the potential modification to BBRs of the same time of day forpreceding days to determine whether the potential modification may beresponsive to an unusual day.

In some cases, the adjustment at block 740 can consider other factors.For example, the adjustment can be based on penalizing a modificationthat increases the probability of the PWD having a hypoglycemic event(e.g., by penalizing modifications that may increase the probability ofthe blood glucose levels of the PWD falling below a threshold low bloodglucose level). In these and other cases, in addition to or in place ofadjusting the BBR, other user-specific dosage-guidelines can beadjusted. For example, ISF and CR can also be adjusted according to thepresent disclosure. In some cases, if BBR is adjusted higher, ISF may beadjusted higher by the same or an approximately proportional percentageamount and CR may be adjusted lower by the same or an approximatelyproportional percentage amount of the BBR.

At block 750, insulin may be delivered during the related diurnal timeperiod based on the adjusted baseline basal insulin rate. For example,the insulin pump can deliver insulin based on the adjusted baselinebasal insulin rate. In some cases, such delivery can include a controldevice (e.g., the control circuitry 240 of FIG. 6B) sending a message tothe insulin pump to deliver insulin.

Modifications, additions, or omissions may be made to the method 700without departing from the scope of the present disclosure. For example,the operations of the method 700 may be implemented in differing order.Additionally or alternatively, two or more operations may be performedat the same time. Furthermore, the outlined operations and actions areprovided as examples, and some of the operations and actions may beoptional, combined into fewer operations and actions, or expanded intoadditional operations and actions without detracting from the essence ofthe disclosed embodiments.

FIG. 9 illustrates a flowchart of an example method 800 of utilizing afear of hypoglycemia index. The method 800 may be performed by anysuitable system, apparatus, or device. For example, the system 10, thepump assembly 15, the mobile computing device 60 of FIG. 1, and/or aremote server may perform one or more of the operations associated withthe method 800. Although illustrated with discrete blocks, the steps andoperations associated with one or more of the blocks of the method 800may be divided into additional blocks, combined into fewer blocks, oreliminated, depending on the desired implementation.

At block 810, an interface can be displayed to a user to input an FHI.For example, an interface can be displayed on a mobile computing device(e.g., the mobile computing device 60 of FIG. 1) and/or to a terminalconnected over a network such as the internet to a remote server. Insome cases, the user (e.g., a PWD or a healthcare professional) can bepresented with an interactive feature from which the user can select theFHI. In these and other cases, the interface can include a variety ofways that the user can input the FHI, such as a preferred blood glucoselevel, a preferred probability of going above or below a certainthreshold, a textual description of a blood glucose level (e.g., “preferhigh”), etc. In these and other cases, the FHI can correspond to athreshold blood glucose level and an acceptable probability of crossingthe threshold blood glucose level. For example, “prefer high” maydesignate a low threshold blood glucose level as 100 mg/dl, with atarget blood glucose level of 150 mg/dl, and a high threshold bloodglucose level of 220 mg/dl, and an acceptable probability of 5% forexceeding either the low or the high threshold values.

At block 820, a probability of a PWD crossing a threshold blood glucoselevel is calculated. For example, a calculation can be made as to howlikely the PWD is to cross the threshold blood glucose levelcorresponding to the FHI. In these and other cases, the probability ofcrossing the threshold can also be compared to the acceptableprobability of crossing the threshold. For example, if the FHI indicatesthat a 5% probability of exceeding a threshold is acceptable, thecalculated probability of exceeding the threshold can be compared to the5% acceptable probability.

At block 830, target blood glucose level can be modified to more closelyalign the probability of crossing the threshold with the FHI. Forexample, if the probability of dropping below a threshold is higher thanthe acceptable probability, the target blood glucose level may beadjusted higher such that the probability is closer to the acceptableprobability. In some cases, the target blood glucose level can beadjusted such that the probability of crossing the threshold is the sameas the acceptable probability. In these and other cases, themodification of the baseline basal insulin rate can also be based on theactual insulin delivered compared to the BBR for a diurnal period. Forexample, if four delivery actions occur during a diurnal time period andeach of them deliver 2× the BBR, the BBR can be modified based on boththe FHI and the 2× delivered. Continuing the example, if a user hadselected a low FHI (e.g., the PWD is not as concerned about going low),the target blood glucose level can be changed by a large amount (e.g.,between 0% and 5%) while if the user had selected a high FHI (e.g., thePWD is concerned about going low), the BBR can be changed be a smalleramount (e.g., between 0% and 2%). In these and other cases, the changeamount can vary depending on whether it is adjusting up or down. Forexample, for a PWD that prefers high blood glucose levels, methods andsystems of the present disclosure can use a larger change when adjustingthe BBR upwards and a lower change when adjusting the BBR downwards. Insome cases, increases to the target blood glucose level can beunconstrained, but decreases constrained to 5% or less, 3% or less, 2%or less, or 1% or less.

At block 840, insulin can be delivered based on the modified targetblood glucose level. For example, a control device can determine insulindelivery profiles or rates based the target blood glucose level(s) usingany suitable method, including the methods described above. In somecases, the delivery of insulin can be based off of one or more insulindelivery profiles that can be generated, and selecting one of theprofiles that most closely approximates a target blood glucose level. Inthese and other cases, the actions of the delivery profiles can be aratio of the modified BBR. For example, the delivery actions can includeone of delivering Ox, lx, or 2 x the modified BBR.

In some cases, the delivery actions of the delivery profiles can bebased off of the FHI as well. For example, for a first FHI (e.g., thePWD is concerned about going low), the possible ratios used in thedelivery actions of the profile can include Ox, 0.5×, lx and 1.5× theBBR (e.g., for a PWD that prefers low), while for a second FHI, thepossible ratios used in the delivery actions of the profile can includeOx, lx, 2×, and 3× (e.g., for a PWD that prefers high).

Modifications, additions, or omissions may be made to the method 800without departing from the scope of the present disclosure. For example,the operations of the method 800 may be implemented in differing order.Additionally or alternatively, two or more operations may be performedat the same time. Furthermore, the outlined operations and actions areprovided as examples, and some of the operations and actions may beoptional, combined into fewer operations and actions, or expanded intoadditional operations and actions without detracting from the essence ofthe disclosed embodiments.

FIG. 10 illustrates a flowchart of an example method 900 of utilizing atemporary override. The method 900 may be performed by any suitablesystem, apparatus, or device. For example, the system 10, the pumpassembly 15, the mobile computing device 60 of FIG. 1, and/or a remoteserver may perform one or more of the operations associated with themethod 900. Although illustrated with discrete blocks, the steps andoperations associated with one or more of the blocks of the method 900may be divided into additional blocks, combined into fewer blocks, oreliminated, depending on the desired implementation.

At block 910, a set of insulin delivery profiles may be generated, eachhaving a series of insulin delivery actions. For example, an electronicdevice (e.g., the pump assembly 15, the mobile computing device 60 ofFIG. 1 and/or a remote server) may generate a set of profiles inaccordance with the present disclosure.

At block 920, an input indicating a temporary override may be received.The temporary override can indicate a user-preferred blood glucose levelfor one or more diurnal periods. For example, a user (e.g., a PWD) maybe presented with a field or other entry component where the user canenter a numerical blood glucose level for a set period of time. Asanother example, the user may be presented with multiple activities(e.g., exercising, driving a car for an extended period of time, etc.)and when the activity will be performed. As another example, the usermay be presented with a series of textual descriptions of preferredblood glucose levels (e.g., “do not go low,” or “do not go high”). Inthese and other cases, the user may be limited in selecting a temporaryoverride for a period of time some point in the future (e.g., at leastthirty minutes in the future).

At block 930, a log of the temporary override can be generated. Forexample, the electronic device can record what was selected for thetemporary override (e.g., a target blood glucose level, a particularactivity, etc.), when, and/or for how long. In some cases, the log maybe updated each time the user inputs a temporary override.

At block 940, a baseline basal insulin rate (BBR) can be temporarilymodified based on the temporary override. For example, the BBR can bemodified to more closely align the BBR with the user-preferred bloodglucose level. For example, the BBR can be adjusted higher if thetemporary override indicates a lower than normal blood glucose level. Asanother example, the BBR can be adjusted lower if the temporary overrideindicates a higher than normal blood glucose level. In some cases, thetemporary override from the block 920 can be received and the BBR can bemodified prior to generating the set of profiles, or the set of profilescan be updated after the temporary override is received and/or the BBRis modified.

At block 950, a determination can be made as to which profile from theset of profiles approximates the user-preferred blood glucose levelduring the diurnal period. For example, a predicted blood glucose levelfor various points in time can be projected based on each of theprofiles. The variation from the user-preferred blood glucose level canbe analyzed, for example, by accumulating the variation over time andfinding the profile with the lowest variation from the user-preferredblood glucose level. In these and other cases, the profile that mostclosely approximates the user-preferred blood glucose level can beselected as the basis for delivery actions of insulin.

At block 960, insulin can be delivered based on the next action in theselected profile. For example, a given profile that was selected mighthave sixteen delivery actions spanning four hours, and the first ofsixteen actions may be taken to deliver insulin. In some cases, theblock 960 can include control circuitry or another control devicegenerating a message to be provided to a pump to deliver insulin inaccordance with the next action in the selected profile.

At block 970, the log can be periodically provided to a healthcareprofessional. For example, the log generated and/or updated at block 930can be sent to a healthcare professional using email, text message, viaan app, etc., such that the healthcare professional can review theoverrides that have occurred for a PWD.

At block 980, the log can be parsed to determine if a pattern is presentin the temporary overrides. For example, the PWD may input a temporaryoverride every Monday, Wednesday, and Friday from 6 PM to 7 PM when theyexercise. As another example, the PWD may input a temporary overrideMonday through Friday from 5:30 PM until 6:15 PM while the PWD driveshome from work. The log can be parsed to find such patterns ofoverrides.

At block 990, the baseline basal insulin rate can be modified for agiven diurnal period based on the pattern. Following the first examplegiven above at block 980, methods and systems of the present disclosurecan adjust the BBR for 6 PM to 7 PM on Monday, Wednesday and Fridaybased on the repeated overrides occurring at those times. Following thesecond example given above at block 980, methods and systems of thepresent disclosure can adjust the BBR from 5:30 PM to 6:15 PM Mondaythrough Friday based on the repeated overrides for that span of time.

Modifications, additions, or omissions may be made to the method 900without departing from the scope of the present disclosure. For example,the operations of the method 900 may be implemented in differing order(e.g., the block 920 can be performed after the block 910, and/or theblocks 970 and/or 980 can be performed any time after the block 930).Additionally or alternatively, two or more operations may be performedat the same time. Furthermore, the outlined operations and actions areprovided as examples, and some of the operations and actions may beoptional (e.g., the blocks 930, 940, 970, 980, and/or 990), combinedinto fewer operations and actions, or expanded into additionaloperations and actions without detracting from the essence of thedisclosed embodiments.

The embodiments described herein may include the use of aspecial-purpose or general-purpose computer including various computerhardware or software modules, as discussed in greater detail below.

Embodiments described herein may be implemented using computer-readablemedia for carrying or having computer-executable instructions or datastructures stored thereon. Such computer-readable media may be anyavailable media that may be accessed by a general-purpose orspecial-purpose computer. By way of example, and not limitation, suchcomputer-readable media may include non-transitory computer-readablestorage media including Random Access Memory (RAM), Read-Only Memory(ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM),Compact Disc Read-Only Memory (CD-ROM) or other optical disk storage,magnetic disk storage or other magnetic storage devices, flash memorydevices (e.g., solid state memory devices), or any other storage mediumwhich may be used to carry or store desired program code in the form ofcomputer-executable instructions or data structures and which may beaccessed by a general-purpose or special-purpose computer. Combinationsof the above may also be included within the scope of computer-readablemedia.

Computer-executable instructions comprise, for example, instructions anddata which cause a general-purpose computer, special-purpose computer,or special-purpose processing device (e.g., one or more processors) toperform a certain function or group of functions. Although the subjectmatter has been described in language specific to structural featuresand/or methodological acts, it is to be understood that the subjectmatter defined in the appended claims is not necessarily limited to thespecific features or acts described above. Rather, the specific featuresand acts described above are disclosed as example forms of implementingthe claims.

As used herein, the terms “module” or “component” may refer to specifichardware implementations configured to perform the operations of themodule or component and/or software objects or software routines thatmay be stored on and/or executed by general-purpose hardware (e.g.,computer-readable media, processing devices, etc.) of the computingsystem. In some embodiments, the different components, modules, engines,and services described herein may be implemented as objects or processesthat execute on the computing system (e.g., as separate threads). Whilesome of the systems and methods described herein are generally describedas being implemented in software (stored on and/or executed bygeneral-purpose hardware), specific hardware implementations or acombination of software and specific hardware implementations are alsopossible and contemplated. In the present description, a “computingentity” may be any computing system as previously defined herein, or anymodule or combination of modulates running on a computing system.

Any ranges expressed herein (including in the claims) are considered tobe given their broadest possible interpretation. For example, unlessexplicitly mentioned otherwise, ranges are to include their end points(e.g., a range of “between X and Y” would include X and Y).Additionally, ranges described using the terms “approximately” or“about” are to be understood to be given their broadest meaningconsistent with the understanding of those skilled in the art.Additionally, the term approximately includes anything within 10%, or5%, or within manufacturing or typical tolerances.

All examples and conditional language recited herein are intended forpedagogical objects to aid the reader in understanding the disclosureand the concepts contributed by the inventor to furthering the art, andare to be construed as being without limitation to such specificallyrecited examples and conditions. Although embodiments of the presentdisclosure have been described in detail, it should be understood thatthe various changes, substitutions, and alterations could be made heretowithout departing from the spirit and scope of the disclosure.

What is claimed is:
 1. A method of providing insulin deliveryinstructions for an insulin delivery device, the method comprising:receiving one or more user-specific dosage parameters; responsive to theone or more user-specific dosage parameters, generating a plurality ofuser-specific basal delivery profile permutations, each user-specificbasal delivery profile permutation having an intended basal rate and anintended delivery time duration for the intended basal rate; selecting afirst user-specific basal delivery profile permutation from theplurality of user-specific basal delivery profile permutations;generating the insulin delivery instructions comprising the intendedbasal rate of the first user-specific basal delivery profile permutationand a variable delivery time duration relative to the intended deliverytime duration of the first user-specific basal delivery profilepermutation; and providing the generated insulin delivery instructionsto the insulin delivery device.
 2. The method of claim 1, furthercomprising: receiving blood glucose level data of a user according to ablood glucose level testing schedule; responsive to the received bloodglucose level data from the user, selecting a second user-specific basaldelivery profile permutation from the plurality of user-specific basaldelivery profile permutations; generating updated insulin deliveryinstructions comprising the intended basal rate of the seconduser-specific basal delivery profile permutation and a second variabledelivery time duration relative to the intended delivery time durationof the second user-specific basal delivery profile permutation; andproviding the generated updated insulin delivery instructions to theinsulin delivery device.
 3. The method of claim 1, wherein the variabledelivery time duration is less than the intended delivery time durationof the first user-specific basal delivery profile permutation.
 4. Themethod of claim 1, wherein the variable delivery time duration is lessthan the intended delivery time duration of the first user-specificbasal delivery profile permutation by one or more hours or by less thansixty minutes.
 5. The method of claim 1, further comprising: responsiveto a loss of receiving up-to-date blood glucose data according to ablood glucose level testing schedule and a passage of the variabledelivery time duration, generating adjusted insulin deliveryinstructions comprising an adjusted basal rate; and providing theadjusted insulin delivery instructions to the insulin delivery device.6. The method of claim 5, wherein the adjusted insulin deliveryinstructions comprise a generic basal rate determined based on thereceived one or more user-specific dosage parameters.
 7. The method ofclaim 1, wherein receiving one or more user-specific dosage parameterscomprises receiving the one or more user-specific dosage parameters at adevice remote to the insulin delivery device.
 8. The method of claim 1,wherein receiving one or more user-specific dosage parameters comprisesreceiving the one or more user-specific dosage parameters via wirelesscommunication.
 9. The method of claim 1, wherein each of the pluralityof user-specific basal delivery profile permutations comprises aprojected effect of the respective user-specific basal delivery profilepermutations on a blood glucose level of a user.
 10. A systemcomprising: a blood glucose monitor; an insulin delivery device; acontroller remote from the blood glucose monitor and the insulindelivery device, the controller configured to: receive one or moreuser-specific dosage parameters; responsive to the one or moreuser-specific dosage parameters, generating a plurality of user-specificbasal delivery profile permutations, each user-specific basal deliveryprofile permutation having an intended basal rate and intended deliverytime duration for the intended basal rate; selecting a firstuser-specific basal delivery profile permutation from the plurality ofuser-specific basal delivery profile permutations; generating insulindelivery instructions comprising the intended basal rate of the firstuser-specific basal delivery profile permutation and a variable deliverytime duration relative to the intended delivery time duration of thefirst user-specific basal delivery profile permutation; and transmittingthe generated insulin delivery instructions to the insulin deliverydevice.
 11. The system of claim 10, wherein the controller furtherconfigured to: receive, from the blood glucose monitor, blood glucoselevel data of a user according to a blood glucose level testingschedule; responsive to the received blood glucose level data the bloodglucose monitor, select a second user-specific basal delivery profilepermutation from the plurality of user-specific basal delivery profilepermutations; generate updated insulin delivery instructions comprisingthe intended basal rate of the second user-specific basal deliveryprofile permutation and a second variable delivery time durationrelative to the intended delivery time duration of the seconduser-specific basal delivery profile permutation; and transmit thegenerated updated insulin delivery instructions to the insulin deliverydevice.
 12. The system of claim 10, wherein the variable delivery timeduration is less than the intended delivery time duration of the firstuser-specific basal delivery profile permutation.
 13. The system ofclaim 10, wherein the variable delivery time duration is less than theintended delivery time duration of the first user-specific basaldelivery profile permutation by one or more hours or by less than sixtyminutes.
 14. The system of claim 10, wherein the controller furtherconfigured to: responsive to a loss of receiving up-to-date bloodglucose data from the blood glucose monitor according to a blood glucoselevel testing schedule and a passage of the variable delivery timeduration, generate adjusted insulin delivery instructions comprising anadjusted basal rate; and transmit the adjusted insulin deliveryinstructions to the insulin delivery device.
 15. The system of claim 14,wherein the adjusted insulin delivery instructions comprise a genericbasal rate determined based on the received one or more user-specificdosage parameters.
 16. The system of claim 10, wherein each of theplurality of user-specific basal delivery profile permutations comprisesa projected effect of the respective user specific basal deliveryprofile permutations on a blood glucose level of a user.
 17. A systemcomprising: an insulin delivery device; a controller remote from theinsulin delivery device and configured to control at least portions ofan operation of the insulin delivery device, the controller configuredto: generate a plurality of user-specific basal delivery profilepermutations, each user-specific basal delivery profile permutationhaving an intended basal rate and an intended delivery time duration forthe intended basal rate, wherein each of the plurality of user-specificbasal delivery profile permutations comprises a projected effect of therespective user-specific basal delivery profile permutation on a bloodglucose level of a user due to the intended delivery time duration andthe intended base rate; responsive to blood glucose data, select a firstuser-specific basal delivery profile permutation from the plurality ofuser-specific basal delivery profile permutations; generate insulindelivery instructions comprising the intended basal rate of the firstuser-specific basal delivery profile permutation and a variable deliverytime duration relative to the intended delivery time duration of thefirst user-specific basal delivery profile permutation; and transmit thegenerated insulin delivery instructions to the insulin delivery deviceto cause the insulin delivery device to deliver insulin to a useraccording to the generated insulin delivery instructions.
 18. The systemof claim 17, wherein the insulin delivery device is configured to revertto an initial baseline basal delivery rate upon passage of the variabledelivery time duration absent new insulin delivery instructions from thecontroller.
 19. The system of claim 17, wherein the variable deliverytime duration is less than the intended delivery time duration of thefirst user-specific basal delivery profile permutation.
 20. The systemof claim 17, wherein the variable delivery time duration is less thanthe intended delivery time duration of the first user-specific basaldelivery profile permutation by one or more hours or by less than sixtyminutes.